CMSIS-DSP: Cleaning of Doxygen comments for new functions.

New distance patterns.

CMSIS/DSP/Include/arm_math.h

@@ -29,27 +29,37 @@
    * ------------
    *
    * This user manual describes the CMSIS DSP software library,
-   * a suite of common signal processing functions for use on Cortex-M processor based devices.
+   * a suite of common signal processing functions for use on Cortex-M and Cortex-A processor 
+   * based devices.
    *
    * The library is divided into a number of functions each covering a specific category:
    * - Basic math functions
    * - Fast math functions
    * - Complex math functions
-   * - Filters
+   * - Filtering functions
    * - Matrix functions
    * - Transform functions
    * - Motor control functions
    * - Statistical functions
    * - Support functions
    * - Interpolation functions
+   * - Support Vector Machine functions (SVM)
+   * - Bayes classifier functions
+   * - Distance functions
    *
-   * The library has separate functions for operating on 8-bit integers, 16-bit integers,
+   * The library has generally separate functions for operating on 8-bit integers, 16-bit integers,
    * 32-bit integer and 32-bit floating-point values.
    *
    * Using the Library
    * ------------
    *
    * The library installer contains prebuilt versions of the libraries in the <code>Lib</code> folder.
+   * Pre-built libraries will not be updated to contain new functions. 
+   * So, SVM, Bayes, Distance functions and experimental functions are not included in those libraries.
+   * If you want to use those functions, you'll have to modify the projects, include the missing
+   * files and rebuild.
+   * You can also use the cmake to build the libraries and select what you want to be included.
+   * Here is the list of pre-built libraries :
    * - arm_cortexM7lfdp_math.lib (Cortex-M7, Little endian, Double Precision Floating Point Unit)
    * - arm_cortexM7bfdp_math.lib (Cortex-M7, Big endian, Double Precision Floating Point Unit)
    * - arm_cortexM7lfsp_math.lib (Cortex-M7, Little endian, Single Precision Floating Point Unit)
@@ -95,6 +105,8 @@
    *
    * The libraries can be built by opening the arm_cortexM_math.uvprojx project in MDK-ARM, selecting a specific target, and defining the optional preprocessor macros detailed above.
    *
+   * There is also a work in progress cmake build. The README file is giving more details.
+   *
    * Preprocessor Macros
    * ------------
    *
@@ -277,17 +289,36 @@
 
 /**
  * @defgroup groupSVM SVM Functions
+ * This set of functions is implementing SVM classification on 2 classes.
+ * The training must be done from scikit-learn. The parameters can be easily
+ * generated from the scikit-learn object. Some examples are given in
+ * DSP/Testing/PatternGeneration/SVM.py
+ *
+ * If more than 2 classes are needed, the functions in this folder 
+ * will have to be used, as building blocks, to do multi-class classification.
+ *
+ * No multi-class classification is provided in this SVM folder.
+ * 
  */
 
 
 /**
  * @defgroup groupBayes Bayesian estimators
  *
+ * Implement the naive gaussian Bayes estimator.
+ * The training must be done from scikit-learn.
+ *
+ * The parameters can be easily
+ * generated from the scikit-learn object. Some examples are given in
+ * DSP/Testing/PatternGeneration/Bayes.py
  */
 
 /**
  * @defgroup groupDistance Distance functions
  *
+ * Distance functions for use with clustering algorithms.
+ * There are distance functions for float vectors and boolean vectors.
+ *
  */
 
 
@@ -7024,9 +7055,9 @@ void arm_svm_linear_init_f32(arm_svm_linear_instance_f32 *S,
 
 /**
  * @brief SVM linear prediction
- * @param[in]    S           points to an instance of the linear SVM structure.
- * @param[in]    in          pointer to input vector
- * @param[out]   pResult     decision value
+ * @param[in]    S          Pointer to an instance of the linear SVM structure.
+ * @param[in]    in         Pointer to input vector
+ * @param[out]   pResult    Decision value
  * @return none.
  *
  */
@@ -7067,13 +7098,12 @@ void arm_svm_polynomial_init_f32(arm_svm_polynomial_instance_f32 *S,
 
 /**
  * @brief SVM polynomial prediction
- * @param[in]    S          points to an instance of the polynomial SVM structure.
- * @param[in]    in         pointer to input vector
- * @param[out]   pResult    decision value
+ * @param[in]    S          Pointer to an instance of the polynomial SVM structure.
+ * @param[in]    in         Pointer to input vector
+ * @param[out]   pResult    Decision value
  * @return none.
  *
  */
-  
 void arm_svm_polynomial_predict_f32(const arm_svm_polynomial_instance_f32 *S, 
    const float32_t * in, 
    int * pResult);
@@ -7105,13 +7135,12 @@ void arm_svm_rbf_init_f32(arm_svm_rbf_instance_f32 *S,
 
 /**
  * @brief SVM rbf prediction
- * @param[in]    S          points to an instance of the rbf SVM structure.
- * @param[in]    in         pointer to input vector
- * @param[out]   pResult    decision value
+ * @param[in]    S         Pointer to an instance of the rbf SVM structure.
+ * @param[in]    in        Pointer to input vector
+ * @param[out]   pResult   decision value
  * @return none.
  *
  */
-  
 void arm_svm_rbf_predict_f32(const arm_svm_rbf_instance_f32 *S, 
    const float32_t * in, 
    int * pResult);
@@ -7144,9 +7173,9 @@ void arm_svm_sigmoid_init_f32(arm_svm_sigmoid_instance_f32 *S,
 
 /**
  * @brief SVM sigmoid prediction
- * @param[in]    S          points to an instance of the rbf SVM structure.
- * @param[in]    in         pointer to input vector
- * @param[out]   pResult    decision value
+ * @param[in]    S        Pointer to an instance of the rbf SVM structure.
+ * @param[in]    in       Pointer to input vector
+ * @param[out]   pResult  Decision value
  * @return none.
  *
  */
@@ -7190,7 +7219,7 @@ uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_ins
  * In probabilistic computations, the dynamic of the probability values can be very
  * wide because they come from gaussian functions.
  * To avoid underflow and overflow issues, the values are represented by their log.
- * In this representation, multiplying the original exp values is easy : their log are added.
+ * In this representation, multiplying the original exp values is easy : their logs are added.
  * But adding the original exp values is requiring some special handling and it is the
  * goal of the LogSumExp function.
  *
@@ -7199,11 +7228,11 @@ uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_ins
  * ln(exp(x1) + ... + exp(xn)) and the computation is done in such a way that
  * rounding issues are minimised.
  *
- * The max xm of the values if extracted and the function is computing:
+ * The max xm of the values is extracted and the function is computing:
  * xm + ln(exp(x1 - xm) + ... + exp(xn - xm))
  *
- * @param[in]    in         points to an array of input values.
- * @param[in]  blockSize     number of samples in the input array.
+ * @param[in]  *in         Pointer to an array of input values.
+ * @param[in]  blockSize   Number of samples in the input array.
  * @return LogSumExp
  *
  */
@@ -7233,9 +7262,9 @@ float32_t arm_logsumexp_dot_prod_f32(const float32_t * pSrcA,
 /**
  * @brief Entropy
  *
- * @param[in]  pSrcA      points to an array of input values.
- * @param[in]  blockSize   number of samples in the input array.
- * @return Entropy -Sum(p ln p)
+ * @param[in]  pSrcA        Array of input values.
+ * @param[in]  blockSize    Number of samples in the input array.
+ * @return     Entropy      -Sum(p ln p)
  *
  */
 
@@ -7246,10 +7275,10 @@ float32_t arm_entropy_f32(const float32_t * pSrcA,uint32_t blockSize);
 /**
  * @brief Kullback-Leibler
  *
- * @param[in]  pSrcA         points to an array of input values for probaility distribution A.
- * @param[in]  pSrcB         points to an array of input values for probaility distribution B.
- * @param[in]  blockSize      number of samples in the input array.
- * @return Kullback-Leibler divergence D(A || B)
+ * @param[in]  pSrcA         Pointer to an array of input values for probability distribution A.
+ * @param[in]  pSrcB         Pointer to an array of input values for probability distribution B.
+ * @param[in]  blockSize     Number of samples in the input array.
+ * @return Kullback-Leibler  Divergence D(A || B)
  *
  */
 float32_t arm_kullback_leibler_f32(const float32_t * pSrcA
@@ -7261,10 +7290,10 @@ float32_t arm_kullback_leibler_f32(const float32_t * pSrcA
  * @brief Weighted sum
  *
  *
- * @param[in]    in         points to an array of input values.
- * @param[in]    weigths    weights
- * @param[in]  blockSize     number of samples in the input array.
- * @return     Weighted sum
+ * @param[in]    *in           Array of input values.
+ * @param[in]    *weigths      Weights
+ * @param[in]    blockSize     Number of samples in the input array.
+ * @return Weighted sum
  *
  */
 float32_t arm_weighted_sum_f32(const float32_t *in
@@ -7276,12 +7305,12 @@ float32_t arm_weighted_sum_f32(const float32_t *in
  * @brief Barycenter
  *
  *
- * @param[in]    in         List of points
- * @param[in]    weights    Weights of the points
+ * @param[in]    in         List of vectors
+ * @param[in]    weights    Weights of the vectors
  * @param[out]   out        Barycenter
- * @param[in]  nbVectors     number of vectors
- * @param[in]  vecDim        Dimension of space
- * @return     None
+ * @param[in]    nbVectors  Number of vectors
+ * @param[in]    vecDim     Dimension of space (vector dimension)
+ * @return       None
  *
  */
 void arm_barycenter_f32(const float32_t *in

CMSIS/DSP/Source/BayesFunctions/arm_gaussian_naive_bayes_predict_f32.c

@@ -28,6 +28,8 @@
 #include <limits.h>
 #include <math.h>
 
+#define PI_F 3.1415926535897932384626433832795f
+#define DPI_F (2*3.1415926535897932384626433832795f)
 
 /**
  * @addtogroup groupBayes
@@ -35,6 +37,10 @@
  */
 
 
+#if defined(ARM_MATH_NEON)
+
+#include "NEMath.h"
+
 /**
  * @brief Naive Gaussian Bayesian Estimator
  *
@@ -45,13 +51,6 @@
  *
  */
 
-#define PI_F 3.1415926535897932384626433832795f
-#define DPI_F (2*3.1415926535897932384626433832795f)
-
-#if defined(ARM_MATH_NEON)
-
-#include "NEMath.h"
-
 uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_instance_f32 *S, 
    const float32_t * in, 
    float32_t *pBuffer)
@@ -235,6 +234,16 @@ uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_ins
 }
 
 #else
+
+/**
+ * @brief Naive Gaussian Bayesian Estimator
+ *
+ * @param[in]  *S         points to a naive bayes instance structure
+ * @param[in]  *in        points to the elements of the input vector.
+ * @param[in]  *pBuffer   points to a buffer of length numberOfClasses
+ * @return The predicted class
+ *
+ */
 uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_instance_f32 *S, 
    const float32_t * in, 
    float32_t *pBuffer)

CMSIS/DSP/Source/DistanceFunctions/arm_boolean_distance.c

@@ -31,28 +31,6 @@
 
 
 
-/**
- * @addtogroup groupDistance
- * @{
- */
-
-
-/**
- * @brief        Elements of boolean distances
- *
- * Different values which are used to compute boolean distances
- *
- * @param[in]    pA              First vector of packed booleans
- * @param[in]    pB              Second vector of packed booleans
- * @param[in]    numberOfBools   Number of booleans
- * @param[out]   cTT             cTT value
- * @param[out]   cTF             cTF value
- * @param[out]   cFT             cFT value
- * @return None
- *
- */
-
-
 
 #if defined(ARM_MATH_NEON)
 
@@ -98,9 +76,3 @@
 #define EXT _TT
 #include "arm_boolean_distance_template.h"
 
-
-
-
-/**
- * @} end of groupDistance group
- */

CMSIS/DSP/Source/DistanceFunctions/arm_braycurtis_distance_f32.c

@@ -32,10 +32,21 @@
 
 
 /**
- * @addtogroup groupDistance
+ * @ingroup groupDistance
  * @{
  */
 
+/**
+ * @defgroup FloatDist Float Distances
+ *
+ * Distances between two vectors of float values.
+ */
+
+/**
+  @addtogroup FloatDist
+  @{
+ */
+
 
 /**
  * @brief        Bray-Curtis distance between two vectors
@@ -125,5 +136,9 @@ float32_t arm_braycurtis_distance_f32(const float32_t *pA,const float32_t *pB, u
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */
+
+/**
+ * @} end of groupDistance group
+ */

CMSIS/DSP/Source/DistanceFunctions/arm_canberra_distance_f32.c

@@ -31,8 +31,8 @@
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -140,5 +140,5 @@ float32_t arm_canberra_distance_f32(const float32_t *pA,const float32_t *pB, uin
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_chebyshev_distance_f32.c

@@ -31,8 +31,8 @@
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -155,5 +155,5 @@ float32_t arm_chebyshev_distance_f32(const float32_t *pA,const float32_t *pB, ui
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_cityblock_distance_f32.c

@@ -30,8 +30,8 @@
 #include <math.h>
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -109,5 +109,5 @@ float32_t arm_cityblock_distance_f32(const float32_t *pA,const float32_t *pB, ui
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_correlation_distance_f32.c

@@ -32,8 +32,8 @@
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -79,5 +79,5 @@ float32_t arm_correlation_distance_f32(float32_t *pA,float32_t *pB, uint32_t blo
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_cosine_distance_f32.c

@@ -31,11 +31,12 @@
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
+
 /**
  * @brief        Cosine distance between two vectors
  *
@@ -64,5 +65,5 @@ float32_t arm_cosine_distance_f32(const float32_t *pA,const float32_t *pB, uint3
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_dice_distance.c

@@ -29,13 +29,6 @@
 #include <limits.h>
 #include <math.h>
 
-
-
-/**
- * @addtogroup groupDistance
- * @{
- */
-
 extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
        , const uint32_t *pB
        , uint32_t numberOfBools
@@ -44,6 +37,30 @@ extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
        , uint32_t *cFT
        );
 
+
+/**
+ * @ingroup groupDistance
+ * @{
+ */
+
+/**
+ * @defgroup BoolDist Boolean Distances
+ *
+ * Distances between two vectors of boolean values.
+ *
+ * Booleans are packed in 32 bit words.
+ * numberOfBooleans argument is the number of booleans and not the
+ * number of words.
+ *
+ * Bits are packed in big-endian mode (because of behavior of numpy packbits in
+ * in version < 1.17)
+ */
+
+/**
+  @addtogroup BoolDist
+  @{
+ */
+
 /**
  * @brief        Dice distance between two vectors
  *
@@ -65,5 +82,9 @@ float32_t arm_dice_distance(const uint32_t *pA, const uint32_t *pB, uint32_t num
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */
+
+/**
+ * @} end of groupDistance group
+ */

CMSIS/DSP/Source/DistanceFunctions/arm_euclidean_distance_f32.c

@@ -32,8 +32,8 @@
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -103,5 +103,5 @@ float32_t arm_euclidean_distance_f32(const float32_t *pA,const float32_t *pB, ui
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_hamming_distance.c

@@ -38,8 +38,8 @@ extern void arm_boolean_distance_TF_FT(const uint32_t *pA
        );
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
 
@@ -64,5 +64,5 @@ float32_t arm_hamming_distance(const uint32_t *pA, const uint32_t *pB, uint32_t
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_jaccard_distance.c

@@ -41,11 +41,10 @@ extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
-
 /**
  * @brief        Jaccard distance between two vectors
  *
@@ -67,5 +66,5 @@ float32_t arm_jaccard_distance(const uint32_t *pA, const uint32_t *pB, uint32_t
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_jensenshannon_distance_f32.c

@@ -30,19 +30,19 @@
 #include <math.h>
 
 
-
-/**
- * @addtogroup groupDistance
- * @{
- */
-
-
 static inline double rel_entr(double x, double y)
 {
     return (x * log(x / y));
 }
 
 
+/**
+  @addtogroup FloatDist
+  @{
+ */
+
+
+
 #if defined(ARM_MATH_NEON)
 
 #include "NEMath.h"
@@ -175,5 +175,5 @@ float32_t arm_jensenshannon_distance_f32(const float32_t *pA,const float32_t *pB
 #endif
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_kulsinski_distance.c

@@ -41,8 +41,8 @@ extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
 
@@ -67,5 +67,5 @@ float32_t arm_kulsinski_distance(const uint32_t *pA, const uint32_t *pB, uint32_
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_minkowski_distance_f32.c

@@ -30,10 +30,9 @@
 #include <math.h>
 
 
-
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup FloatDist
+  @{
  */
 
 
@@ -116,5 +115,5 @@ float32_t arm_minkowski_distance_f32(const float32_t *pA,const float32_t *pB, in
 
 
 /**
- * @} end of groupDistance group
+ * @} end of FloatDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_rogerstanimoto_distance.c

@@ -42,11 +42,10 @@ extern void arm_boolean_distance_TT_FF_TF_FT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
-
 /**
  * @brief        Roger Stanimoto distance between two vectors
  *
@@ -70,5 +69,5 @@ float32_t arm_rogerstanimoto_distance(const uint32_t *pA, const uint32_t *pB, ui
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_russellrao_distance.c

@@ -39,11 +39,10 @@ extern void arm_boolean_distance_TT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
-
 /**
  * @brief        Russell-Rao distance between two vectors
  *
@@ -67,5 +66,5 @@ float32_t arm_russellrao_distance(const uint32_t *pA, const uint32_t *pB, uint32
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_sokalmichener_distance.c

@@ -41,11 +41,10 @@ extern void arm_boolean_distance_TT_FF_TF_FT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
-
 /**
  * @brief        Sokal-Michener distance between two vectors
  *
@@ -71,5 +70,5 @@ float32_t arm_sokalmichener_distance(const uint32_t *pA, const uint32_t *pB, uin
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_sokalsneath_distance.c

@@ -40,11 +40,10 @@ extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
 
 
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
-
 /**
  * @brief        Sokal-Sneath distance between two vectors
  *
@@ -69,5 +68,5 @@ float32_t arm_sokalsneath_distance(const uint32_t *pA, const uint32_t *pB, uint3
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/DistanceFunctions/arm_yule_distance.c

@@ -39,10 +39,9 @@ extern void arm_boolean_distance_TT_FF_TF_FT(const uint32_t *pA
        , uint32_t *cFT
        );
 
-
 /**
- * @addtogroup groupDistance
- * @{
+  @addtogroup BoolDist
+  @{
  */
 
 
@@ -69,5 +68,5 @@ float32_t arm_yule_distance(const uint32_t *pA, const uint32_t *pB, uint32_t num
 
 
 /**
- * @} end of groupDistance group
+ * @} end of BoolDist group
  */

CMSIS/DSP/Source/SVMFunctions/arm_svm_linear_init_f32.c

@@ -31,11 +31,6 @@
 /**
  * @defgroup groupSVM SVM Functions
  *
- * Computes SVM predictions. 
- *
- * The SVM predictors in CMSIS-DSP are only working with 2 classes.
- * Multi-class support must be built from the building blocks provided by CMSIS-DSP.
- *
  */
 
 
@@ -47,6 +42,10 @@
 
 /**
  * @brief        SVM linear instance init function
+ *
+ * Classes are integer used as output of the function (instead of having -1,1
+ * as class values).
+ *
  * @param[in]    S                      Parameters for the SVM function
  * @param[in]    nbOfSupportVectors     Number of support vectors
  * @param[in]    vectorDimension        Dimension of vector space

CMSIS/DSP/Source/SVMFunctions/arm_svm_linear_predict_f32.c

@@ -37,9 +37,9 @@
 
 /**
  * @brief SVM linear prediction
- * @param[in]    S          points to an instance of the linear SVM structure.
- * @param[in]    in         pointer to input vector
- * @param[out]   pResult    decision value
+ * @param[in]    S          Pointer to an instance of the linear SVM structure.
+ * @param[in]    in         Pointer to input vector
+ * @param[out]   pResult    Decision value
  * @return none.
  *
  */

CMSIS/DSP/Source/SVMFunctions/arm_svm_polynomial_init_f32.c

@@ -38,6 +38,10 @@
 
 /**
  * @brief        SVM polynomial instance init function
+ *
+ * Classes are integer used as output of the function (instead of having -1,1
+ * as class values).
+ *
  * @param[in]    S                      points to an instance of the polynomial SVM structure.
  * @param[in]    nbOfSupportVectors     Number of support vectors
  * @param[in]    vectorDimension        Dimension of vector space

CMSIS/DSP/Source/SVMFunctions/arm_svm_polynomial_predict_f32.c

@@ -38,9 +38,9 @@
 
 /**
  * @brief SVM polynomial prediction
- * @param[in]    S          points to an instance of the polynomial SVM structure.
- * @param[in]    in         pointer to input vector
- * @param[out]   pResult    decision value
+ * @param[in]    S          Pointer to an instance of the polynomial SVM structure.
+ * @param[in]    in         Pointer to input vector
+ * @param[out]   pResult    Decision value
  * @return none.
  *
  */

CMSIS/DSP/Source/SVMFunctions/arm_svm_rbf_init_f32.c

@@ -37,6 +37,10 @@
 
 /**
  * @brief        SVM radial basis function instance init function
+ *
+ * Classes are integer used as output of the function (instead of having -1,1
+ * as class values).
+ *
  * @param[in]    S                      points to an instance of the polynomial SVM structure.
  * @param[in]    nbOfSupportVectors     Number of support vectors
  * @param[in]    vectorDimension        Dimension of vector space

CMSIS/DSP/Source/SVMFunctions/arm_svm_rbf_predict_f32.c

@@ -37,8 +37,8 @@
 
 /**
  * @brief SVM rbf prediction
- * @param[in]    S         points to an instance of the rbf SVM structure.
- * @param[in]    in        pointer to input vector
+ * @param[in]    S         Pointer to an instance of the rbf SVM structure.
+ * @param[in]    in        Pointer to input vector
  * @param[out]   pResult   decision value
  * @return none.
  *

CMSIS/DSP/Source/SVMFunctions/arm_svm_sigmoid_init_f32.c

@@ -37,6 +37,10 @@
 
 /**
  * @brief        SVM sigmoid instance init function
+ *
+ * Classes are integer used as output of the function (instead of having -1,1
+ * as class values).
+ *
  * @param[in]    S                      points to an instance of the rbf SVM structure.
  * @param[in]    nbOfSupportVectors     Number of support vectors
  * @param[in]    vectorDimension        Dimension of vector space

CMSIS/DSP/Source/SVMFunctions/arm_svm_sigmoid_predict_f32.c

@@ -37,9 +37,9 @@
 
 /**
  * @brief SVM sigmoid prediction
- * @param[in]    S        points to an instance of the rbf SVM structure.
- * @param[in]    in       pointer to input vector
- * @param[out]   pResult  decision value
+ * @param[in]    S        Pointer to an instance of the rbf SVM structure.
+ * @param[in]    in       Pointer to input vector
+ * @param[out]   pResult  Decision value
  * @return none.
  *
  */

CMSIS/DSP/Source/StatisticsFunctions/arm_entropy_f32.c

@@ -38,12 +38,9 @@
 /**
  * @brief Entropy
  *
- * Distribution may contain 0 probabilities with Neon version.
- * Result will be right but some exception flags will be set.
- *
- * @param[in]  *pSrcA         points to an array of input values.
- * @param[in]  blockSize   number of samples in the input array.
- * @return Entropy -Sum(p ln p)
+ * @param[in]  pSrcA        Array of input values.
+ * @param[in]  blockSize    Number of samples in the input array.
+ * @return     Entropy      -Sum(p ln p)
  *
  */
 

CMSIS/DSP/Source/StatisticsFunctions/arm_logsumexp_f32.c

@@ -41,7 +41,7 @@
  * In probabilistic computations, the dynamic of the probability values can be very
  * wide because they come from gaussian functions.
  * To avoid underflow and overflow issues, the values are represented by their log.
- * In this representation, multiplying the original exp values is easy : their log are added.
+ * In this representation, multiplying the original exp values is easy : their logs are added.
  * But adding the original exp values is requiring some special handling and it is the
  * goal of the LogSumExp function.
  *
@@ -50,11 +50,11 @@
  * ln(exp(x1) + ... + exp(xn)) and the computation is done in such a way that
  * rounding issues are minimised.
  *
- * The max xm of the values if extracted and the function is computing:
+ * The max xm of the values is extracted and the function is computing:
  * xm + ln(exp(x1 - xm) + ... + exp(xn - xm))
  *
- * @param[in]    *in         points to an array of input values.
- * @param[in]  blockSize     number of samples in the input array.
+ * @param[in]  *in         Pointer to an array of input values.
+ * @param[in]  blockSize   Number of samples in the input array.
  * @return LogSumExp
  *
  */

CMSIS/DSP/Source/SupportFunctions/arm_barycenter_f32.c

@@ -38,12 +38,12 @@
  * @brief Barycenter
  *
  *
- * @param[in]    *in         List of points
- * @param[in]    *weights    Weights of the points
+ * @param[in]    *in         List of vectors
+ * @param[in]    *weights    Weights of the vectors
  * @param[out]   *out        Barycenter
- * @param[in]  nbVectors     number of vectors
- * @param[in]  vecDim        Dimension of space
- * @return     None
+ * @param[in]    nbVectors   Number of vectors
+ * @param[in]    vecDim      Dimension of space (vector dimension)
+ * @return       None
  *
  */
 

CMSIS/DSP/Source/SupportFunctions/arm_weighted_sum_f32.c

@@ -39,10 +39,10 @@
  * @brief Weighted sum
  *
  *
- * @param[in]    *in         points to an array of input values.
- * @param[in]    *weigths    weights
- * @param[in]  blockSize     number of samples in the input array.
- * @return     Weighted sum
+ * @param[in]    *in           Array of input values.
+ * @param[in]    *weigths      Weights
+ * @param[in]    blockSize     Number of samples in the input array.
+ * @return       Weighted sum
  *
  */
 

CMSIS/DSP/Testing/PatternGeneration/Distance.py

@@ -7,7 +7,7 @@ import scipy.spatial
 
 NBTESTSAMPLES = 10
 
-VECDIM = [12,14,20]
+VECDIM = [35,14,20]
 
 def euclidean(xa,xb):
         r = scipy.spatial.distance.euclidean(xa,xb)

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Dims1_s16.txt

@@ -2,5 +2,5 @@ H
 2
 // 10
 0x000A
-// 12
-0x000C
+// 35
+0x0023

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Dims9_s16.txt

@@ -2,25 +2,25 @@ H
 12
 // 10
 0x000A
-// 12
-0x000C
-// 3
-0x0003
+// 35
+0x0023
 // 4
 0x0004
 // 2
 0x0002
-// 4
-0x0004
-// 4
-0x0004
-// 3
-0x0003
-// 4
-0x0004
+// 2
+0x0002
+// 2
+0x0002
 // 2
 0x0002
 // 3
 0x0003
+// 2
+0x0002
 // 4
 0x0004
+// 3
+0x0003
+// 3
+0x0003

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/InputA1_f32.txt

@@ -1,242 +1,702 @@
 W
-120
-// -0.178487
-0xbe36c55b
-// 0.482719
-0x3ef726ff
-// 0.128451
-0x3e0388ca
-// 0.866186
-0x3f5dbe58
-// -1.523149
-0xbfc2f68b
-// 0.605613
-0x3f1b0973
-// -1.227975
-0xbf9d2e4d
-// -0.591868
-0xbf1784ac
-// -1.497882
-0xbfbfba97
-// -0.282963
-0xbe90e093
-// -0.706497
-0xbf34dcfa
-// -0.755151
-0xbf415192
-// -0.558170
-0xbf0ee435
-// -1.027751
-0xbf838d59
-// 0.998202
-0x3f7f8a2b
-// 0.206976
-0x3e53f16b
-// 0.656722
-0x3f281ef3
-// 0.426181
-0x3eda345f
-// -1.456604
-0xbfba71fc
-// 0.008399
-0x3c099be7
-// -1.641694
-0xbfd2230b
-// -0.404196
-0xbecef2d1
-// -0.031733
-0xbd01fa33
-// -0.307805
-0xbe9d98ac
-// 0.955540
-0x3f749e40
-// 0.007134
-0x3be9c275
-// -0.446252
-0xbee47b14
-// -1.106664
-0xbf8da729
-// 0.307716
-0x3e9d8ce8
-// -1.823099
-0xbfe95b51
-// 0.889152
-0x3f639f7e
-// -0.164237
-0xbe282dc3
-// 0.568792
-0x3f119c53
-// 1.149142
-0x3f931719
-// -0.114768
-0xbdeb0b53
-// 0.560862
-0x3f0f94aa
-// 1.364221
-0x3fae9ecb
-// -0.033868
-0xbd0ab97b
-// 1.955365
-0x3ffa4964
-// -1.071076
-0xbf891906
-// -0.080529
-0xbda4ec98
-// 0.119819
-0x3df563d2
-// 2.041473
-0x4002a77d
-// 0.144665
-0x3e142326
-// 0.402286
-0x3ecdf878
-// 0.558718
-0x3f0f081f
-// 0.838104
-0x3f568dfb
-// 1.100654
-0x3f8ce23e
-// 1.341633
-0x3fabbaa0
-// -2.521938
-0xc021676d
-// -0.384021
-0xbec49e5c
-// -0.333633
-0xbeaad1f6
-// 0.295935
-0x3e9784d6
-// 0.035576
-0x3d11b88b
-// 0.923338
-0x3f6c5fdc
-// 2.130540
-0x40085ac6
-// 0.200980
-0x3e4dcdbe
-// 1.345594
-0x3fac3c6f
-// 0.851886
-0x3f5a1532
-// 0.833798
-0x3f5573c7
-// -0.882113
-0xbf61d223
-// 0.715873
-0x3f37436f
-// -0.527723
-0xbf0718df
-// 0.916126
-0x3f6a8738
-// 0.552950
-0x3f0d8e24
-// -0.812670
-0xbf500b27
-// 0.263209
-0x3e86c34a
-// 0.655730
-0x3f27dde6
-// -0.100891
-0xbdcea002
-// 0.622843
-0x3f1f72a8
-// -0.011502
-0xbc3c733b
-// -0.748668
-0xbf3fa8bb
-// -0.635873
-0xbf22c894
-// 0.559467
-0x3f0f393d
-// -0.009196
-0xbc16abfd
-// 1.304398
-0x3fa6f683
-// 0.992219
-0x3f7e0217
-// -1.385024
-0xbfb14875
-// 1.137760
-0x3f91a21c
-// 0.475164
-0x3ef348ba
-// -0.788306
-0xbf49ce74
-// -0.979564
-0xbf7ac4b3
-// -0.701340
-0xbf338b0b
-// -0.659470
-0xbf28d307
-// -0.959309
-0xbf75954a
-// -0.931897
-0xbf6e90cd
-// -0.118577
-0xbdf2d850
-// 0.172273
-0x3e306868
-// -0.915819
-0xbf6a731f
-// -0.234015
-0xbe6fa1b7
-// 0.536514
-0x3f0958fc
-// -0.522399
-0xbf05bbf5
-// -0.042109
-0xbd2c7a8f
-// 1.030601
-0x3f83eabc
-// 0.073388
-0x3d964c81
-// 1.004056
-0x3f8084e7
-// 0.424424
-0x3ed94e18
-// -1.192672
-0xbf98a97c
-// -0.667152
-0xbf2aca76
-// 0.704874
-0x3f34729b
-// -0.428180
-0xbedb3a74
-// -0.411661
-0xbed2c538
-// 0.377093
-0x3ec11263
-// 2.336006
-0x40158120
-// 0.282322
-0x3e908c7b
-// -2.082379
-0xc00545b2
-// 0.590898
-0x3f174510
-// -0.700579
-0xbf335928
-// -2.064212
-0xc0041c0e
-// -0.482730
-0xbef72861
-// -0.850502
-0xbf59ba7a
-// 2.296297
-0x4012f688
-// 0.552692
-0x3f0d7d34
-// 1.610890
-0x3fce31a1
-// -1.047689
-0xbf861ab0
-// -0.525026
-0xbf066816
-// 0.064286
-0x3d83a859
-// 0.472272
-0x3ef1cd9d
-// -0.279714
-0xbe8f36b4
-// 0.495461
-0x3efdad15
+350
+// -1.452491
+0xbfb9eb39
+// 1.893648
+0x3ff2630f
+// -1.098358
+0xbf8c9702
+// 1.494444
+0x3fbf49f5
+// 1.153991
+0x3f93b5fd
+// -0.190421
+0xbe42fdae
+// 0.663564
+0x3f29df5c
+// -0.090187
+0xbdb8b437
+// 0.680821
+0x3f2e4a4c
+// -0.115829
+0xbded37aa
+// 0.637944
+0x3f23504e
+// -0.713865
+0xbf36bfe1
+// -0.813447
+0xbf503e0a
+// 0.315312
+0x3ea1708f
+// -0.254808
+0xbe82762f
+// 0.059849
+0x3d7523d9
+// -0.592295
+0xbf17a0a6
+// 0.248753
+0x3e7eb909
+// -0.776635
+0xbf46d18b
+// -0.908865
+0xbf68ab5b
+// -1.911781
+0xbff4b539
+// -1.122272
+0xbf8fa69a
+// 0.360390
+0x3eb884fe
+// 0.858513
+0x3f5bc77a
+// 1.202874
+0x3f99f7c5
+// 0.086360
+0x3db0dd93
+// 0.518316
+0x3f04b05d
+// -1.677063
+0xbfd6aa03
+// 0.214889
+0x3e5c0bcb
+// 0.736129
+0x3f3c72fa
+// -1.897915
+0xbff2eee4
+// 1.207474
+0x3f9a8e82
+// -0.297553
+0xbe9858e0
+// -0.694411
+0xbf31c4e5
+// 1.344387
+0x3fac14e2
+// -0.321686
+0xbea4b403
+// 2.135153
+0x4008a659
+// 0.883625
+0x3f62353b
+// 0.725255
+0x3f39aa55
+// -0.746871
+0xbf3f32f8
+// -2.542470
+0xc022b7d5
+// -0.174657
+0xbe32d92f
+// 2.880440
+0x40385920
+// -0.059511
+0xbd73c149
+// -0.348299
+0xbeb25446
+// -0.145571
+0xbe1510a1
+// -0.843685
+0xbf57fbba
+// 0.574525
+0x3f13141a
+// 1.070569
+0x3f890869
+// 0.251237
+0x3e80a22f
+// 1.068576
+0x3f88c71b
+// 0.067318
+0x3d89ddd6
+// 1.603882
+0x3fcd4bfe
+// 1.116346
+0x3f8ee46c
+// -0.571589
+0xbf1253a2
+// 0.388227
+0x3ec6c5b3
+// 0.916816
+0x3f6ab47b
+// 0.668293
+0x3f2b1539
+// -0.571612
+0xbf125531
+// 0.725642
+0x3f39c3b4
+// 0.583429
+0x3f155b9c
+// -0.037266
+0xbd18a486
+// 0.003738
+0x3b74f88a
+// -0.025453
+0xbcd082d2
+// -0.477903
+0xbef4afc0
+// 1.563412
+0x3fc81de1
+// 0.598850
+0x3f194e3d
+// -0.225393
+0xbe66cd76
+// 1.396119
+0x3fb2b408
+// 0.892111
+0x3f64615d
+// 0.362100
+0x3eb9652a
+// 2.067757
+0x40045622
+// 0.632343
+0x3f21e142
+// 0.259713
+0x3e84f91a
+// -1.493871
+0xbfbf372d
+// 0.012721
+0x3c506a12
+// -0.668525
+0xbf2b2476
+// -1.266768
+0xbfa22576
+// 0.957851
+0x3f7535c1
+// -0.344096
+0xbeb02d58
+// 1.010041
+0x3f814906
+// 0.482116
+0x3ef6d7dc
+// 1.449145
+0x3fb97d93
+// 0.414550
+0x3ed43fe2
+// -0.976960
+0xbf7a1a08
+// 1.017604
+0x3f8240d7
+// 1.081378
+0x3f8a6a9a
+// 1.685380
+0x3fd7ba86
+// -0.775604
+0xbf468e01
+// -0.269178
+0xbe89d1b2
+// 1.078199
+0x3f8a026c
+// 0.740269
+0x3f3d823d
+// 1.285671
+0x3fa490db
+// 0.307842
+0x3e9d9d71
+// -1.101490
+0xbf8cfd9f
+// -0.774085
+0xbf462a6c
+// 1.293270
+0x3fa589e0
+// 0.974298
+0x3f796b98
+// 1.482730
+0x3fbdca16
+// 0.370167
+0x3ebd8697
+// -1.206749
+0xbf9a76c1
+// 0.489602
+0x3efaad1e
+// -0.278665
+0xbe8ead20
+// 1.066520
+0x3f8883ba
+// 0.557594
+0x3f0ebe80
+// 0.271160
+0x3e8ad579
+// -0.176799
+0xbe350ace
+// -0.201274
+0xbe4e1ac8
+// -0.196537
+0xbe4940f1
+// -0.146331
+0xbe15d7bd
+// -1.334847
+0xbfaadc46
+// 0.398398
+0x3ecbfadd
+// -0.765888
+0xbf441142
+// -1.624741
+0xbfcff782
+// -0.089441
+0xbdb72c97
+// 0.803355
+0x3f4da8ab
+// -0.434841
+0xbedea370
+// -0.829015
+0xbf543a53
+// 0.108811
+0x3dded873
+// -0.618105
+0xbf1e3c27
+// -0.565698
+0xbf10d195
+// -1.236510
+0xbf9e45f5
+// 0.784639
+0x3f48de15
+// -0.441905
+0xbee2416b
+// 0.713072
+0x3f368be4
+// -0.408830
+0xbed15230
+// 0.030698
+0x3cfb79d7
+// 1.041270
+0x3f854858
+// -0.338476
+0xbead4cbd
+// -0.195899
+0xbe4899b7
+// -0.606672
+0xbf1b4ed4
+// -1.384262
+0xbfb12f81
+// -1.329434
+0xbfaa2ae1
+// 0.064219
+0x3d838552
+// 0.964240
+0x3f76d86a
+// 0.125467
+0x3e007a65
+// 1.238280
+0x3f9e7ff3
+// 0.605874
+0x3f1b1a96
+// 1.078595
+0x3f8a0f68
+// -0.573599
+0xbf12d75e
+// -1.965302
+0xbffb8f01
+// -2.092720
+0xc005ef20
+// -0.178645
+0xbe36ee9f
+// 0.276759
+0x3e8db34b
+// 0.696631
+0x3f325663
+// 1.565554
+0x3fc86412
+// -0.781196
+0xbf47fc78
+// 0.478930
+0x3ef53645
+// 0.433459
+0x3eddee5b
+// -2.164999
+0xc00a8f56
+// 1.488682
+0x3fbe8d24
+// -0.685820
+0xbf2f91e4
+// 0.449910
+0x3ee65a91
+// 0.584374
+0x3f159988
+// 2.584748
+0x40256c84
+// -0.981780
+0xbf7b55e7
+// 0.213704
+0x3e5ad53d
+// -0.726775
+0xbf3a0ded
+// 1.768916
+0x3fe26bd9
+// -0.495292
+0xbefd96f7
+// -0.433985
+0xbede3355
+// -0.854315
+0xbf5ab468
+// 0.437991
+0x3ee04069
+// 1.077265
+0x3f89e3d1
+// 0.561330
+0x3f0fb356
+// -1.998649
+0xbfffd3bc
+// 0.094521
+0x3dc1940d
+// -0.325862
+0xbea6d75f
+// 2.063243
+0x40040c2c
+// -1.406081
+0xbfb3fa78
+// 0.167870
+0x3e2be60f
+// 0.406130
+0x3ecff055
+// -0.385055
+0xbec525f7
+// -0.571454
+0xbf124acc
+// -0.185670
+0xbe3e2055
+// 1.060238
+0x3f87b5dd
+// 1.036375
+0x3f84a7ee
+// -0.046171
+0xbd3d1e0a
+// 0.525701
+0x3f069452
+// 0.271649
+0x3e8b1587
+// -0.671162
+0xbf2bd146
+// 1.450450
+0x3fb9a855
+// -0.197414
+0xbe4a26ee
+// -1.989525
+0xbffea8bf
+// -0.791059
+0xbf4a82d2
+// -0.847300
+0xbf58e8a1
+// -0.204101
+0xbe50fff8
+// 0.044962
+0x3d3829ad
+// 0.342890
+0x3eaf8f3e
+// -0.633985
+0xbf224cd3
+// -0.758306
+0xbf422056
+// -1.401149
+0xbfb358d8
+// -1.716303
+0xbfdbafd0
+// 0.323620
+0x3ea5b185
+// -0.007778
+0xbbfedf35
+// -0.165336
+0xbe294dec
+// 0.109410
+0x3de01241
+// -1.253928
+0xbfa080b6
+// 0.748492
+0x3f3f9d30
+// 1.689326
+0x3fd83bd8
+// -0.992343
+0xbf7e0a38
+// -0.214921
+0xbe5c1458
+// -0.092430
+0xbdbd4be7
+// 0.976374
+0x3f79f3aa
+// -1.922200
+0xbff60aa5
+// 0.794053
+0x3f4b470c
+// -0.203297
+0xbe502d25
+// 0.015774
+0x3c813846
+// 0.750269
+0x3f40119d
+// 0.403117
+0x3ece6569
+// -1.435010
+0xbfb7ae65
+// 0.952504
+0x3f73d752
+// -0.451800
+0xbee75254
+// 0.213701
+0x3e5ad45e
+// -0.825370
+0xbf534b6e
+// 0.298141
+0x3e98a5ea
+// 0.027673
+0x3ce2b2d0
+// -1.006789
+0xbf80de79
+// 0.245970
+0x3e7bdf95
+// -0.546056
+0xbf0bca54
+// -0.569876
+0xbf11e36d
+// -0.316834
+0xbea23817
+// -0.772978
+0xbf45e1e3
+// 0.361147
+0x3eb8e849
+// 1.377834
+0x3fb05cdf
+// 1.053762
+0x3f86e1ae
+// -0.584607
+0xbf15a8d3
+// -0.704629
+0xbf34628a
+// 1.136285
+0x3f9171c9
+// -2.454969
+0xc01d1e37
+// 0.438466
+0x3ee07e94
+// 0.409850
+0x3ed1d7d5
+// -0.726579
+0xbf3a011d
+// 1.166696
+0x3f95564f
+// 1.075305
+0x3f89a398
+// 0.409966
+0x3ed1e710
+// 0.660913
+0x3f293195
+// -0.545591
+0xbf0babe1
+// -0.220605
+0xbe61e62f
+// -1.291064
+0xbfa54199
+// -0.930677
+0xbf6e40d3
+// -0.285571
+0xbe92364d
+// 0.489434
+0x3efa970e
+// -0.687964
+0xbf301e64
+// 0.613639
+0x3f1d1770
+// -0.286367
+0xbe929eb7
+// -0.584810
+0xbf15b622
+// -1.764649
+0xbfe1e004
+// 0.581880
+0x3f14f615
+// -0.275275
+0xbe8cf0e5
+// -1.383755
+0xbfb11ee3
+// 0.854623
+0x3f5ac88d
+// -0.457541
+0xbeea42da
+// -1.872357
+0xbfefa961
+// -1.294354
+0xbfa5ad65
+// -1.865689
+0xbfeecee3
+// -2.153707
+0xc009d655
+// 0.018523
+0x3c97bca0
+// -0.000522
+0xba08ba9b
+// 0.863130
+0x3f5cf60f
+// 0.809198
+0x3f4f279f
+// 0.058604
+0x3d700a47
+// -0.171652
+0xbe2fc593
+// -0.887889
+0xbf634cb9
+// 0.540221
+0x3f0a4bf1
+// 0.113028
+0x3de77b15
+// 1.182266
+0x3f97547c
+// 0.963639
+0x3f76b104
+// -0.497876
+0xbefee99d
+// 0.796604
+0x3f4bee3e
+// 0.021098
+0x3cacd5b3
+// -1.442425
+0xbfb8a160
+// 0.693637
+0x3f31922e
+// -1.307007
+0xbfa74bff
+// 0.964705
+0x3f76f6ed
+// 1.219444
+0x3f9c16bf
+// -0.461242
+0xbeec27f7
+// 0.787784
+0x3f49ac3d
+// -0.812665
+0xbf500ac9
+// -0.579913
+0xbf147528
+// 0.861180
+0x3f5c764c
+// 1.160611
+0x3f948ee9
+// 1.128945
+0x3f908146
+// 1.257488
+0x3fa0f55b
+// -0.506345
+0xbf019fd7
+// -0.601016
+0xbf19dc34
+// -1.598532
+0xbfcc9cb2
+// -2.086799
+0xc0058e1e
+// -0.939411
+0xbf707d3d
+// 0.063259
+0x3d818dd2
+// -0.042495
+0xbd2e0ef2
+// 1.866845
+0x3feef4c8
+// -0.113030
+0xbde77c10
+// 2.074325
+0x4004c1be
+// -0.495297
+0xbefd978d
+// 1.111551
+0x3f8e474c
+// -1.615089
+0xbfcebb3d
+// -1.959054
+0xbffac24b
+// -0.379349
+0xbec239fb
+// -0.317062
+0xbea255fb
+// -0.330564
+0xbea93fb4
+// 0.566829
+0x3f111bb2
+// 0.652374
+0x3f2701fb
+// -1.079735
+0xbf8a34c4
+// 0.566904
+0x3f11209f
+// 0.901286
+0x3f66bab3
+// 2.046517
+0x4002fa20
+// 2.103147
+0x400699f5
+// 0.562442
+0x3f0ffc31
+// 0.681061
+0x3f2e5a04
+// -0.079670
+0xbda32a1d
+// 1.898958
+0x3ff31110
+// -1.521270
+0xbfc2b8fa
+// 1.500615
+0x3fc0142a
+// 0.035490
+0x3d115e06
+// 0.908816
+0x3f68a832
+// -0.504079
+0xbf010b53
+// -0.122442
+0xbdfac2b6
+// -0.716809
+0xbf3780c4
+// 0.278403
+0x3e8e8ad2
+// 0.397040
+0x3ecb48c7
+// -1.284357
+0xbfa465d4
+// -0.032200
+0xbd03e426
+// -0.816683
+0xbf51121f
+// -0.210216
+0xbe5742f0
+// -1.951360
+0xbff9c62e
+// -0.002563
+0xbb27f7da
+// -0.443620
+0xbee3221c
+// 0.604428
+0x3f1abbd3
+// -1.501276
+0xbfc029d4
+// -0.411867
+0xbed2e038
+// -1.018003
+0xbf824ded
+// 2.233709
+0x400ef517
+// -1.903603
+0xbff3a946
+// -0.623919
+0xbf1fb926
+// 0.187763
+0x3e4044f6
+// -0.219931
+0xbe613596
+// 0.270580
+0x3e8a8972
+// 1.411761
+0x3fb4b492
+// -0.130883
+0xbe06061a
+// -0.225559
+0xbe66f90f
+// 0.421052
+0x3ed7941f
+// 1.032253
+0x3f8420df
+// 0.081124
+0x3da62426
+// 0.796595
+0x3f4bed9f
+// -0.068979
+0xbd8d450b
+// -0.426926
+0xbeda960e
+// 1.198597
+0x3f996ba2
+// -0.519480
+0xbf04fcac
+// 0.330711
+0x3ea95302

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/InputA8_f32.txt

@@ -1,242 +1,702 @@
 W
-120
-// 0.020175
-0x3ca54615
-// 0.054563
-0x3d5f7de3
-// 0.014519
-0x3c6de266
-// 0.097908
-0x3dc883f2
-// 0.172167
-0x3e304c78
-// 0.068454
-0x3d8c31de
-// 0.138802
-0x3e0e222d
-// 0.066901
-0x3d890353
-// 0.169311
-0x3e2d5fc8
-// 0.031984
-0x3d0301fb
-// 0.079858
-0x3da38c75
-// 0.085357
-0x3daecfcd
-// 0.072260
-0x3d93fd33
-// 0.133052
-0x3e083ec7
-// 0.129227
-0x3e0453f9
-// 0.026795
-0x3cdb810a
-// 0.085019
-0x3dae1e5a
-// 0.055173
-0x3d61fd2c
-// 0.188571
-0x3e4118bd
-// 0.001087
-0x3a8e84a6
-// 0.212533
-0x3e59a22b
-// 0.052327
-0x3d5654d2
-// 0.004108
-0x3b869d3f
-// 0.039848
-0x3d2337f5
-// 0.118065
-0x3df1cbe7
-// 0.000881
-0x3a67102d
-// 0.055138
-0x3d61d861
-// 0.136737
-0x3e0c04dd
-// 0.038021
-0x3d1bbbaa
-// 0.225259
-0x3e66aa39
-// 0.109862
-0x3de0ff55
-// 0.020293
-0x3ca63d23
-// 0.070279
-0x3d8fee57
-// 0.141986
-0x3e1164bf
-// 0.014180
-0x3c68553f
-// 0.069299
-0x3d8decad
-// 0.140485
-0x3e0fdb5c
-// 0.003488
-0x3b6491e9
-// 0.201360
-0x3e4e3160
-// 0.110298
-0x3de1e3bc
-// 0.008293
-0x3c07de75
-// 0.012339
-0x3c4a28a7
-// 0.210227
-0x3e5745df
-// 0.014897
-0x3c741436
-// 0.041427
-0x3d29af21
-// 0.057536
-0x3d6baaaf
-// 0.086307
-0x3db0c17e
-// 0.113344
-0x3de820ac
-// 0.119801
-0x3df55a12
-// 0.225196
-0x3e6699b2
-// 0.034291
-0x3d0c74bc
-// 0.029792
-0x3cf40daa
-// 0.026425
-0x3cd87a35
-// 0.003177
-0x3b503192
-// 0.082449
-0x3da8db1c
-// 0.190246
-0x3e42cfd7
-// 0.017946
-0x3c930476
-// 0.120154
-0x3df61388
-// 0.076069
-0x3d9bca03
-// 0.074454
-0x3d987b33
-// 0.129526
-0x3e04a28b
-// 0.105116
-0x3dd7472b
-// 0.077489
-0x3d9eb28f
-// 0.134521
-0x3e09bfc9
-// 0.081193
-0x3da648a4
-// 0.119330
-0x3df46315
-// 0.038649
-0x3d1e4e06
-// 0.096285
-0x3dc53114
-// 0.014814
-0x3c72b880
-// 0.091456
-0x3dbb4d56
-// 0.001689
-0x3add5eec
-// 0.109932
-0x3de123ee
-// 0.066046
-0x3d8742f1
-// 0.058110
-0x3d6e0464
-// 0.000955
-0x3a7a6523
-// 0.135483
-0x3e0abbfa
-// 0.103058
-0x3dd3100a
-// 0.143857
-0x3e134f3f
-// 0.118175
-0x3df2058b
-// 0.049353
-0x3d4a26d7
-// 0.081878
-0x3da7afd0
-// 0.101743
-0x3dd05ee0
-// 0.072845
-0x3d953002
-// 0.068497
-0x3d8c47ee
-// 0.146662
-0x3e162e88
-// 0.142471
-0x3e11e3ec
-// 0.018128
-0x3c9481dd
-// 0.026338
-0x3cd7c200
-// 0.140013
-0x3e0f5f91
-// 0.035777
-0x3d128ad2
-// 0.082024
-0x3da7fc14
-// 0.079866
-0x3da390b7
-// 0.006438
-0x3bd2f3c9
-// 0.157561
-0x3e2157b8
-// 0.011220
-0x3c37d32b
-// 0.153503
-0x3e1d2fdc
-// 0.041617
-0x3d2a76fa
-// 0.116949
-0x3def82df
-// 0.065418
-0x3d85fa0b
-// 0.069117
-0x3d8d8d51
-// 0.041986
-0x3d2bf935
-// 0.040366
-0x3d2556b1
-// 0.036976
-0x3d17747c
-// 0.229060
-0x3e6a8ea3
-// 0.027683
-0x3ce2c844
-// 0.204190
-0x3e511730
-// 0.057941
-0x3d6d53ae
-// 0.068696
-0x3d8cb089
-// 0.192167
-0x3e44c763
-// 0.044940
-0x3d38127f
-// 0.079177
-0x3da22793
-// 0.213773
-0x3e5ae73a
-// 0.051453
-0x3d52bfef
-// 0.149965
-0x3e19906d
-// 0.097534
-0x3dc7bffc
-// 0.048877
-0x3d483345
-// 0.005985
-0x3bc41b0c
-// 0.043966
-0x3d34159c
-// 0.026040
-0x3cd5518c
-// 0.046125
-0x3d3ced46
+350
+// 0.051350
+0x3d5254d5
+// 0.066947
+0x3d891b6a
+// 0.038831
+0x3d1f0ce6
+// 0.052834
+0x3d586815
+// 0.040797
+0x3d271b40
+// 0.006732
+0x3bdc9840
+// 0.023459
+0x3cc02d94
+// 0.003188
+0x3b50f4fe
+// 0.024069
+0x3cc52d04
+// 0.004095
+0x3b862ed5
+// 0.022553
+0x3cb8c20d
+// 0.025238
+0x3ccebef4
+// 0.028758
+0x3ceb960d
+// 0.011147
+0x3c36a350
+// 0.009008
+0x3c13979d
+// 0.002116
+0x3b0aaa15
+// 0.020940
+0x3cab8991
+// 0.008794
+0x3c1015bd
+// 0.027457
+0x3ce0ecc6
+// 0.032131
+0x3d039c3d
+// 0.067588
+0x3d8a6b82
+// 0.039676
+0x3d228363
+// 0.012741
+0x3c50bf90
+// 0.030351
+0x3cf8a34b
+// 0.042526
+0x3d2e2f5c
+// 0.003053
+0x3b4816dc
+// 0.018324
+0x3c961caa
+// 0.059290
+0x3d72d9e3
+// 0.007597
+0x3bf8f095
+// 0.026025
+0x3cd531a5
+// 0.067098
+0x3d896a83
+// 0.042688
+0x3d2ed9e3
+// 0.010520
+0x3c2c59fc
+// 0.024550
+0x3cc91c8e
+// 0.047529
+0x3d42ad5c
+// 0.011824
+0x3c41baa2
+// 0.078482
+0x3da0bb56
+// 0.032480
+0x3d050954
+// 0.026658
+0x3cda62ac
+// 0.027453
+0x3ce0e4f7
+// 0.093454
+0x3dbf64e6
+// 0.006420
+0x3bd25df9
+// 0.105877
+0x3dd8d60a
+// 0.002187
+0x3b0f5b2d
+// 0.012803
+0x3c51c1a4
+// 0.005351
+0x3baf55bb
+// 0.031012
+0x3cfe0bde
+// 0.021118
+0x3cacff96
+// 0.039351
+0x3d212eae
+// 0.009235
+0x3c174d85
+// 0.039278
+0x3d20e1de
+// 0.002474
+0x3b2229b8
+// 0.058954
+0x3d717a03
+// 0.041034
+0x3d28130a
+// 0.021010
+0x3cac1d33
+// 0.014270
+0x3c69cd5c
+// 0.033700
+0x3d0a08a1
+// 0.024565
+0x3cc93bac
+// 0.021011
+0x3cac1f08
+// 0.026673
+0x3cda8084
+// 0.021445
+0x3cafaded
+// 0.001370
+0x3ab38b09
+// 0.000137
+0x3910123b
+// 0.000936
+0x3a7541d9
+// 0.017566
+0x3c8fe76c
+// 0.057467
+0x3d6b6232
+// 0.022012
+0x3cb452a9
+// 0.008285
+0x3c07bd16
+// 0.051317
+0x3d523246
+// 0.032792
+0x3d065066
+// 0.011976
+0x3c443802
+// 0.068390
+0x3d8c0ffc
+// 0.020914
+0x3cab54a6
+// 0.008590
+0x3c0cbc77
+// 0.049409
+0x3d4a6102
+// 0.000421
+0x39dc94f3
+// 0.022111
+0x3cb5224a
+// 0.041898
+0x3d2b9cd6
+// 0.031680
+0x3d01c348
+// 0.011381
+0x3c3a766a
+// 0.033407
+0x3d08d545
+// 0.015946
+0x3c82a08a
+// 0.047930
+0x3d4451d8
+// 0.013711
+0x3c60a414
+// 0.032312
+0x3d0459fa
+// 0.033657
+0x3d09db8e
+// 0.035766
+0x3d127f52
+// 0.055743
+0x3d6452b8
+// 0.025653
+0x3cd22586
+// 0.008903
+0x3c11dd7d
+// 0.035661
+0x3d12110f
+// 0.024484
+0x3cc89290
+// 0.042523
+0x3d2e2c64
+// 0.010182
+0x3c26d118
+// 0.036431
+0x3d1538d0
+// 0.025602
+0x3cd1bc21
+// 0.042774
+0x3d2f33f4
+// 0.032224
+0x3d03fdaa
+// 0.049040
+0x3d48de9a
+// 0.012243
+0x3c48972b
+// 0.039913
+0x3d237b50
+// 0.016193
+0x3c84a7d0
+// 0.009217
+0x3c170182
+// 0.035275
+0x3d107c04
+// 0.018442
+0x3c9713e6
+// 0.012480
+0x3c4c79d2
+// 0.008137
+0x3c055202
+// 0.009264
+0x3c17c6c3
+// 0.009046
+0x3c143444
+// 0.006735
+0x3bdcb097
+// 0.061437
+0x3d7ba518
+// 0.018336
+0x3c963638
+// 0.035250
+0x3d10628e
+// 0.074779
+0x3d9925d4
+// 0.004117
+0x3b86e3ed
+// 0.036975
+0x3d1772bb
+// 0.020014
+0x3ca3f3b7
+// 0.038156
+0x3d1c491c
+// 0.005008
+0x3ba41ac0
+// 0.028448
+0x3ce90ccb
+// 0.026036
+0x3cd54a54
+// 0.056911
+0x3d691b3b
+// 0.036113
+0x3d13eb78
+// 0.020339
+0x3ca69d9c
+// 0.032819
+0x3d066d96
+// 0.018817
+0x3c9a2520
+// 0.001413
+0x3ab93026
+// 0.047925
+0x3d444cc5
+// 0.015578
+0x3c7f3ccf
+// 0.009016
+0x3c13b91f
+// 0.027922
+0x3ce4bd2e
+// 0.063711
+0x3d827af5
+// 0.061188
+0x3d7a9fd3
+// 0.002956
+0x3b41b47f
+// 0.044379
+0x3d35c732
+// 0.005775
+0x3bbd394a
+// 0.056992
+0x3d6970a5
+// 0.027886
+0x3ce4703d
+// 0.049643
+0x3d4b561c
+// 0.026400
+0x3cd844ec
+// 0.062225
+0x3d7ee003
+// 0.066260
+0x3d87b327
+// 0.005656
+0x3bb95804
+// 0.008763
+0x3c0f9187
+// 0.022057
+0x3cb4b046
+// 0.049569
+0x3d4b0862
+// 0.024734
+0x3cca9f6b
+// 0.015164
+0x3c7871db
+// 0.013724
+0x3c60db5f
+// 0.068548
+0x3d8c62f9
+// 0.047135
+0x3d41103f
+// 0.021714
+0x3cb1e26f
+// 0.014245
+0x3c696401
+// 0.018502
+0x3c97926d
+// 0.081838
+0x3da79ad1
+// 0.031085
+0x3cfea628
+// 0.006766
+0x3bddb7cb
+// 0.023011
+0x3cbc81db
+// 0.056007
+0x3d656804
+// 0.015682
+0x3c807769
+// 0.013741
+0x3c612141
+// 0.027049
+0x3cdd9688
+// 0.013868
+0x3c633542
+// 0.034108
+0x3d0bb531
+// 0.017773
+0x3c919853
+// 0.063281
+0x3d819993
+// 0.002993
+0x3b44215f
+// 0.010317
+0x3c290a75
+// 0.065326
+0x3d85c9d5
+// 0.044519
+0x3d3659e4
+// 0.005315
+0x3bae2a36
+// 0.012859
+0x3c52ae1f
+// 0.012192
+0x3c47bf56
+// 0.018093
+0x3c943888
+// 0.005879
+0x3bc0a201
+// 0.043009
+0x3d302a6d
+// 0.042041
+0x3d2c3366
+// 0.001873
+0x3af57e48
+// 0.021325
+0x3caeb292
+// 0.011020
+0x3c348b8c
+// 0.027226
+0x3cdf094d
+// 0.058838
+0x3d71008b
+// 0.008008
+0x3c0334f4
+// 0.080706
+0x3da5495d
+// 0.032090
+0x3d037097
+// 0.034371
+0x3d0cc8de
+// 0.008280
+0x3c07a6c3
+// 0.001824
+0x3aef0fd2
+// 0.013910
+0x3c63e4d7
+// 0.025718
+0x3cd2ae8b
+// 0.030761
+0x3cfbfed5
+// 0.056838
+0x3d68cf7b
+// 0.069623
+0x3d8e9676
+// 0.013128
+0x3c571633
+// 0.000316
+0x39a56cb7
+// 0.006707
+0x3bdbc62a
+// 0.004438
+0x3b916efb
+// 0.050866
+0x3d505946
+// 0.030363
+0x3cf8bbf6
+// 0.068529
+0x3d8c58b9
+// 0.040255
+0x3d24e279
+// 0.008718
+0x3c0ed7b6
+// 0.003749
+0x3b75b9d1
+// 0.039607
+0x3d223b35
+// 0.077975
+0x3d9fb17e
+// 0.032211
+0x3d03eff4
+// 0.008247
+0x3c071ded
+// 0.000640
+0x3a27bd84
+// 0.030435
+0x3cf95317
+// 0.016353
+0x3c85f622
+// 0.056746
+0x3d686e97
+// 0.037666
+0x3d1a4788
+// 0.017866
+0x3c925bb8
+// 0.008451
+0x3c0a745b
+// 0.032638
+0x3d05afe8
+// 0.011790
+0x3c412990
+// 0.001094
+0x3a8f6ee7
+// 0.039813
+0x3d231276
+// 0.009727
+0x3c1f5c8b
+// 0.021593
+0x3cb0e45c
+// 0.022535
+0x3cb89bca
+// 0.012529
+0x3c4d460b
+// 0.030567
+0x3cfa66f9
+// 0.014281
+0x3c69fbca
+// 0.054485
+0x3d5f2bd0
+// 0.041670
+0x3d2aae2f
+// 0.023118
+0x3cbd616a
+// 0.027864
+0x3ce442c4
+// 0.044933
+0x3d380bfd
+// 0.097079
+0x3dc6d193
+// 0.017339
+0x3c8e09e9
+// 0.016207
+0x3c84c4cb
+// 0.028732
+0x3ceb5f27
+// 0.046136
+0x3d3cf8ff
+// 0.042522
+0x3d2e2b76
+// 0.016212
+0x3c84ce6e
+// 0.026135
+0x3cd6196b
+// 0.021575
+0x3cb0bdd5
+// 0.008724
+0x3c0eed6f
+// 0.051054
+0x3d511de9
+// 0.036803
+0x3d16be73
+// 0.011293
+0x3c3904a9
+// 0.019354
+0x3c9e8cae
+// 0.027205
+0x3cdedcc0
+// 0.024266
+0x3cc6c900
+// 0.010024
+0x3c243bd0
+// 0.020471
+0x3ca7b24e
+// 0.061770
+0x3d7d027e
+// 0.020368
+0x3ca6db2f
+// 0.009636
+0x3c1ddf57
+// 0.048437
+0x3d4665fe
+// 0.029915
+0x3cf510ef
+// 0.016016
+0x3c83339e
+// 0.065540
+0x3d8639ec
+// 0.045308
+0x3d399494
+// 0.065307
+0x3d85bf8e
+// 0.075389
+0x3d9a6554
+// 0.000648
+0x3a29f715
+// 0.000018
+0x37992785
+// 0.030213
+0x3cf7816b
+// 0.028325
+0x3ce80a62
+// 0.002051
+0x3b067031
+// 0.006009
+0x3bc4e332
+// 0.031080
+0x3cfe9b04
+// 0.018910
+0x3c9ae911
+// 0.003956
+0x3b81a4fb
+// 0.041384
+0x3d29826e
+// 0.033731
+0x3d0a29d7
+// 0.017428
+0x3c8ec48d
+// 0.027884
+0x3ce46dd9
+// 0.000739
+0x3a4198ff
+// 0.050491
+0x3d4ecf6e
+// 0.024280
+0x3cc6e722
+// 0.045751
+0x3d3b64fb
+// 0.033769
+0x3d0a50fe
+// 0.042686
+0x3d2ed70c
+// 0.016145
+0x3c844350
+// 0.027576
+0x3ce1e669
+// 0.028447
+0x3ce908d7
+// 0.020299
+0x3ca64ac4
+// 0.024815
+0x3ccb4807
+// 0.033443
+0x3d08fb24
+// 0.032530
+0x3d053e5e
+// 0.036234
+0x3d146a32
+// 0.014590
+0x3c6f0b9b
+// 0.017318
+0x3c8ddea8
+// 0.046061
+0x3d3caaa3
+// 0.060130
+0x3d764b52
+// 0.027069
+0x3cddbf6c
+// 0.001823
+0x3aeeea60
+// 0.001224
+0x3aa07e71
+// 0.053793
+0x3d5c558d
+// 0.003257
+0x3b5571e4
+// 0.059771
+0x3d74d26d
+// 0.014272
+0x3c69d455
+// 0.032029
+0x3d0330cf
+// 0.046538
+0x3d3e9ee6
+// 0.056450
+0x3d673798
+// 0.010931
+0x3c33171e
+// 0.009136
+0x3c15af58
+// 0.009525
+0x3c1c0f27
+// 0.016333
+0x3c85ccc1
+// 0.018798
+0x3c99fe23
+// 0.031112
+0x3cfedf0b
+// 0.016335
+0x3c85d14c
+// 0.025970
+0x3cd4bf99
+// 0.058970
+0x3d718a35
+// 0.060601
+0x3d783943
+// 0.016207
+0x3c84c3a7
+// 0.019625
+0x3ca0c3a9
+// 0.002296
+0x3b1672f2
+// 0.054718
+0x3d601fd4
+// 0.043835
+0x3d338c37
+// 0.043240
+0x3d311c26
+// 0.001023
+0x3a8609ea
+// 0.039026
+0x3d1fd981
+// 0.021646
+0x3cb15295
+// 0.005258
+0x3bac49b3
+// 0.030781
+0x3cfc27d5
+// 0.011955
+0x3c43dedc
+// 0.017049
+0x3c8bab34
+// 0.055152
+0x3d61e715
+// 0.001383
+0x3ab53c13
+// 0.035069
+0x3d0fa4fa
+// 0.009027
+0x3c13e5d8
+// 0.083794
+0x3dab9c32
+// 0.000110
+0x38e6cf11
+// 0.019050
+0x3c9c0df1
+// 0.025955
+0x3cd49f80
+// 0.064467
+0x3d84072c
+// 0.017686
+0x3c90e277
+// 0.043714
+0x3d330de0
+// 0.095918
+0x3dc470e3
+// 0.081743
+0x3da76902
+// 0.026792
+0x3cdb7ab3
+// 0.008063
+0x3c0419d1
+// 0.009444
+0x3c1abb8c
+// 0.011619
+0x3c3e5dde
+// 0.060623
+0x3d784fb1
+// 0.005620
+0x3bb82a48
+// 0.009686
+0x3c1eb149
+// 0.018081
+0x3c941d9f
+// 0.044326
+0x3d358f85
+// 0.003484
+0x3b644c62
+// 0.034207
+0x3d0c1c76
+// 0.002962
+0x3b421f34
+// 0.018333
+0x3c962e9c
+// 0.051469
+0x3d52d188
+// 0.022307
+0x3cb6bd8c
+// 0.014201
+0x3c68ac19

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/InputB1_f32.txt

@@ -1,242 +1,702 @@
 W
-120
-// -0.828562
-0xbf541c9c
-// 2.004161
-0x4000442d
-// 0.735416
-0x3f3c443d
-// 1.458402
-0x3fbaacec
-// 0.698616
-0x3f32d884
-// -1.003043
-0xbf8063b3
-// 0.226180
-0x3e679bb8
-// -0.389370
-0xbec75b7c
-// 2.176395
-0x400b4a10
-// -0.550549
-0xbf0cf0cf
-// -0.925676
-0xbf6cf916
-// 0.349005
-0x3eb2b0d4
-// 1.570787
-0x3fc90f88
-// 1.019942
-0x3f828d76
-// 0.916706
-0x3f6aad3d
-// 0.182143
-0x3e3a83b4
-// 0.067746
-0x3d8abe32
-// -0.555449
-0xbf0e31ed
-// -0.552240
-0xbf0d5fa1
-// 0.133172
-0x3e085e4d
-// -0.946715
-0xbf725bea
-// -0.302952
-0xbe9b1c90
-// 0.426966
-0x3eda9b58
-// -0.558919
-0xbf0f1549
-// -0.467335
-0xbeef4690
-// -0.723536
-0xbf3939ae
-// -0.093326
-0xbdbf21a3
-// -1.745742
-0xbfdf7478
-// 1.046713
-0x3f85faaf
-// 0.781418
-0x3f480b04
-// -0.985286
-0xbf7c3bb4
-// -0.471733
-0xbef1870a
-// -0.374430
-0xbebfb543
-// -0.577605
-0xbf13dde4
-// -1.409534
-0xbfb46b9d
-// -0.737478
-0xbf3ccb58
-// -1.680687
-0xbfd720c4
-// -0.617566
-0xbf1e18c6
-// -2.852123
-0xc036892d
-// -0.133018
-0xbe0835d3
-// 0.710461
-0x3f35e0c4
-// 1.106881
-0x3f8dae47
-// 0.019177
-0x3c9d19f5
-// 0.208392
-0x3e5564b0
-// -0.635991
-0xbf22d04f
-// -0.863174
-0xbf5cf8f2
-// 0.586601
-0x3f162b83
-// -1.738018
-0xbfde775f
-// 1.051694
-0x3f869de5
-// 1.450912
-0x3fb9b77a
-// 0.168458
-0x3e2c8020
-// -0.217289
-0xbe5e80e9
-// -1.407255
-0xbfb420ee
-// -1.815471
-0xbfe86159
-// 1.098959
-0x3f8caab3
-// 0.188220
-0x3e40bca1
-// -0.647777
-0xbf25d4bf
-// -0.314524
-0xbea10947
-// -0.637166
-0xbf231d4e
-// 1.098990
-0x3f8cabb6
-// -0.099688
-0xbdcc2931
-// 0.604458
-0x3f1abdcb
-// 1.483376
-0x3fbddf40
-// 0.080634
-0x3da52334
-// -1.293237
-0xbfa588c8
-// -1.531264
-0xbfc40077
-// 0.916514
-0x3f6aa0a9
-// -0.833330
-0xbf55551e
-// -1.782696
-0xbfe42f65
-// -1.045796
-0xbf85dca6
-// 0.614467
-0x3f1d4db0
-// -0.837290
-0xbf56589d
-// -0.030267
-0xbcf7f2c2
-// 0.697974
-0x3f32ae6b
-// -0.253202
-0xbe81a3ba
-// 0.185480
-0x3e3dee79
-// -1.107341
-0xbf8dbd58
-// 1.436646
-0x3fb7e401
-// 1.617052
-0x3fcefb8c
-// -1.258732
-0xbfa11e21
-// 0.243038
-0x3e78defd
-// 1.121516
-0x3f8f8dd5
-// 0.745664
-0x3f3ee3d0
-// -0.218248
-0xbe5f7c70
-// -1.296925
-0xbfa601a8
-// 0.313480
-0x3ea08083
-// 1.367711
-0x3faf1126
-// 0.456621
-0x3ee9ca48
-// -0.681353
-0xbf2e6d25
-// -0.235936
-0xbe719956
-// 1.364807
-0x3faeb203
-// 0.129441
-0x3e048c19
-// 0.515201
-0x3f03e43e
-// 0.607140
-0x3f1b6d89
-// -1.636634
-0xbfd17d3b
-// 0.655813
-0x3f27e358
-// -0.175897
-0xbe341e71
-// -0.716399
-0xbf3765f0
-// -0.608448
-0xbf1bc344
-// 1.456762
-0x3fba772c
-// 0.941742
-0x3f7115fe
-// -0.975837
-0xbf79d06e
-// 0.072625
-0x3d94bc56
-// -1.034785
-0xbf8473d7
-// -0.597662
-0xbf190068
-// -0.658336
-0xbf2888bb
-// -1.309196
-0xbfa793b9
-// 0.786471
-0x3f495622
-// 0.409138
-0x3ed17a89
-// 1.519091
-0x3fc2718f
-// 0.185946
-0x3e3e68ad
-// -0.341489
-0xbeaed799
-// -0.954036
-0xbf743bb8
-// 1.565450
-0x3fc860aa
-// 0.427405
-0x3edad4cf
-// -1.080225
-0xbf8a44d0
-// -0.910396
-0xbf690fbc
-// 0.956431
-0x3f74d8a6
-// 0.011845
-0x3c421151
-// -0.841074
-0xbf57509c
+350
+// -2.491502
+0xc01f74c7
+// 2.095556
+0x40061d98
+// -0.408440
+0xbed11f02
+// -0.551564
+0xbf0d3353
+// -0.414227
+0xbed41584
+// 0.351392
+0x3eb3e997
+// 2.327236
+0x4014f16f
+// -1.106229
+0xbf8d98ea
+// -1.665396
+0xbfd52bb0
+// -1.344827
+0xbfac234a
+// -0.663616
+0xbf29e2c2
+// -1.031643
+0xbf840ce2
+// 1.340773
+0x3fab9e74
+// -1.746148
+0xbfdf81c5
+// 0.479551
+0x3ef587a8
+// -2.834611
+0xc0356a43
+// -2.166066
+0xc00aa0d4
+// 0.159061
+0x3e22e0d7
+// -1.237173
+0xbf9e5bab
+// 0.186270
+0x3e3ebd97
+// -0.166998
+0xbe2b01a2
+// 0.141906
+0x3e114fd8
+// -0.787598
+0xbf49a008
+// 0.640078
+0x3f23dc25
+// 0.293128
+0x3e9614de
+// 0.046832
+0x3d3fd264
+// 0.407293
+0x3ed088ae
+// 1.533558
+0x3fc44b9e
+// -0.850610
+0xbf59c198
+// 1.803891
+0x3fe6e5e5
+// 0.884616
+0x3f627634
+// 0.149109
+0x3e18affd
+// 0.201781
+0x3e4e9f90
+// 0.825334
+0x3f534911
+// 0.124657
+0x3dff4bf3
+// -0.181090
+0xbe396f8a
+// 1.391368
+0x3fb2185a
+// -1.125600
+0xbf9013aa
+// 2.493606
+0x401f973e
+// 0.423191
+0x3ed8ac86
+// 0.179609
+0x3e37eb8b
+// 0.062359
+0x3d7f6c95
+// 0.754384
+0x3f411f4e
+// 0.901866
+0x3f66e0ac
+// 0.764434
+0x3f43b1f1
+// -1.361045
+0xbfae36ba
+// -0.252298
+0xbe812d3b
+// 0.755285
+0x3f415a61
+// -1.406653
+0xbfb40d32
+// 0.376288
+0x3ec0a8ce
+// -0.959230
+0xbf759018
+// -0.144865
+0xbe145768
+// 0.305648
+0x3e9c7dee
+// -2.681561
+0xc02b9eb2
+// 0.149901
+0x3e197fb3
+// -1.872817
+0xbfefb87c
+// -1.093837
+0xbf8c02d9
+// 0.310436
+0x3e9ef17b
+// -0.326203
+0xbea70415
+// -0.052951
+0xbd58e322
+// -0.047466
+0xbd426b75
+// -0.259214
+0xbe84b7c1
+// -1.105579
+0xbf8d8399
+// 0.923408
+0x3f6c6479
+// -0.770638
+0xbf454887
+// -3.135115
+0xc048a5b8
+// -0.080555
+0xbda4f9cc
+// 0.065765
+0x3d86afdc
+// 1.159904
+0x3f9477b8
+// -1.414054
+0xbfb4ffbc
+// -0.636860
+0xbf230946
+// 0.888272
+0x3f6365d3
+// -2.532316
+0xc0221177
+// -0.448819
+0xbee5cb8a
+// 0.918582
+0x3f6b2838
+// 0.477383
+0x3ef46b98
+// 2.719043
+0x402e04cc
+// 0.022009
+0x3cb44b42
+// -0.078776
+0xbda15575
+// 1.104884
+0x3f8d6cda
+// -0.568996
+0xbf11a9bd
+// 1.718671
+0x3fdbfd6c
+// -0.697026
+0xbf32704e
+// 0.201829
+0x3e4eac61
+// -0.665552
+0xbf2a6196
+// 0.748097
+0x3f3f8346
+// -1.046017
+0xbf85e3e6
+// 1.196713
+0x3f992de0
+// 1.858983
+0x3fedf32b
+// -1.838823
+0xbfeb5e8d
+// -0.666615
+0xbf2aa74b
+// -0.647230
+0xbf25b0e0
+// -0.172125
+0xbe30418e
+// 0.574236
+0x3f130129
+// -0.696307
+0xbf324129
+// -0.973329
+0xbf792c1a
+// -1.269150
+0xbfa2737e
+// 0.021253
+0x3cae1a9d
+// -0.209878
+0xbe56ea58
+// 1.209804
+0x3f9adadc
+// 2.152378
+0x4009c08e
+// -1.569336
+0xbfc8e000
+// -1.083601
+0xbf8ab36e
+// 0.115620
+0x3decca38
+// -0.078628
+0xbda107ee
+// -0.141694
+0xbe111828
+// 0.689849
+0x3f3099e9
+// -0.022192
+0xbcb5cc36
+// -0.907916
+0xbf686d27
+// -0.205213
+0xbe522375
+// -0.363012
+0xbeb9dcc4
+// 0.622957
+0x3f1f7a19
+// -1.364653
+0xbfaeacf4
+// 0.741801
+0x3f3de6af
+// -0.720616
+0xbf387a4d
+// -0.583052
+0xbf1542e5
+// -1.490034
+0xbfbeb96f
+// 0.675104
+0x3f2cd3a2
+// 0.148884
+0x3e187513
+// -0.257958
+0xbe841308
+// -0.285342
+0xbe921855
+// -0.500465
+0xbf001e7d
+// -1.350147
+0xbfacd19a
+// -0.115520
+0xbdec95f9
+// 1.153730
+0x3f93ad6f
+// 1.664769
+0x3fd51728
+// -1.038673
+0xbf84f33d
+// -2.118076
+0xc0078e8e
+// 0.968117
+0x3f77d68b
+// -0.381260
+0xbec33479
+// 0.056674
+0x3d682338
+// 0.743058
+0x3f3e3911
+// 1.000084
+0x3f8002c1
+// -0.038328
+0xbd1cfde0
+// -0.657030
+0xbf283321
+// 1.274683
+0x3fa328d2
+// 0.632207
+0x3f21d856
+// -1.427221
+0xbfb6af2a
+// 1.047308
+0x3f860e2e
+// -1.893568
+0xbff2606e
+// 0.346031
+0x3eb12aea
+// 1.057576
+0x3f875ea7
+// 2.407194
+0x401a0f76
+// 1.891943
+0x3ff22b2d
+// 3.251111
+0x40501236
+// 0.264409
+0x3e876090
+// 0.858025
+0x3f5ba78a
+// -0.049446
+0xbd4a87a1
+// 0.042077
+0x3d2c586c
+// 0.847101
+0x3f58db9c
+// -0.063880
+0xbd82d3af
+// 2.707460
+0x402d4708
+// 1.342670
+0x3fabdc9f
+// -0.146883
+0xbe166871
+// 0.239676
+0x3e756d84
+// -0.570153
+0xbf11f592
+// 1.223729
+0x3f9ca323
+// -1.161937
+0xbf94ba5a
+// -1.214825
+0xbf9b7f64
+// 0.468593
+0x3eefeb5d
+// 1.179348
+0x3f96f4dd
+// -0.031477
+0xbd00ee7d
+// -1.201408
+0xbf99c7b9
+// -1.615085
+0xbfcebb18
+// -0.724525
+0xbf397a7f
+// 0.776445
+0x3f46c518
+// -0.965027
+0xbf770c03
+// 0.631033
+0x3f218b5f
+// 1.476255
+0x3fbcf5eb
+// -0.120247
+0xbdf643fe
+// -0.305774
+0xbe9c8e60
+// 0.452766
+0x3ee7d102
+// 1.025039
+0x3f833479
+// -0.837033
+0xbf5647c8
+// 1.047662
+0x3f8619c9
+// -0.135562
+0xbe0ad0cd
+// -0.212267
+0xbe595c9c
+// -0.530458
+0xbf07cc20
+// 1.485325
+0x3fbe1f24
+// 0.084959
+0x3dadff17
+// 1.297029
+0x3fa6050e
+// 0.859775
+0x3f5c1a2f
+// 0.268158
+0x3e894c06
+// -0.737768
+0xbf3cde63
+// -1.094090
+0xbf8c0b25
+// 1.005688
+0x3f80ba60
+// 0.057914
+0x3d6d36cd
+// -0.414303
+0xbed41f84
+// -0.040436
+0xbd259ff3
+// -0.387620
+0xbec6761e
+// -0.668527
+0xbf2b248f
+// -1.403108
+0xbfb3990f
+// -1.416605
+0xbfb5534c
+// 0.197056
+0x3e49c929
+// 0.048182
+0x3d455adf
+// -0.907007
+0xbf68319a
+// -0.184339
+0xbe3cc375
+// 0.258364
+0x3e84484e
+// -1.648254
+0xbfd2f9fb
+// 1.828103
+0x3fe9ff47
+// -0.925930
+0xbf6d09ba
+// 1.400427
+0x3fb34135
+// 2.217661
+0x400dee26
+// 0.335065
+0x3eab8d9f
+// 0.557191
+0x3f0ea412
+// -0.504350
+0xbf011d10
+// 0.579353
+0x3f14507c
+// 0.452526
+0x3ee7b178
+// -0.059090
+0xbd720816
+// 0.751179
+0x3f404d4c
+// -0.684649
+0xbf2f452a
+// -1.288991
+0xbfa4fdaa
+// 0.188521
+0x3e410ba4
+// 0.591383
+0x3f1764dc
+// 0.157823
+0x3e219c57
+// -1.027153
+0xbf8379c2
+// 0.991405
+0x3f7dccbb
+// 1.035790
+0x3f8494c3
+// 0.410985
+0x3ed26ca9
+// 0.234350
+0x3e6ff95f
+// -0.787204
+0xbf498631
+// -0.535904
+0xbf0930fa
+// -0.957165
+0xbf7508cb
+// 1.180295
+0x3f9713e5
+// 1.213448
+0x3f9b5244
+// 0.063175
+0x3d816209
+// 0.610853
+0x3f1c60d7
+// 0.765379
+0x3f43efe5
+// -1.410292
+0xbfb48470
+// 0.369563
+0x3ebd375d
+// 0.020988
+0x3cabef5a
+// -0.888917
+0xbf639011
+// 0.606971
+0x3f1b6279
+// 1.380946
+0x3fb0c2d3
+// -0.073971
+0xbd977ded
+// -1.084300
+0xbf8aca56
+// 0.556052
+0x3f0e596d
+// 0.304574
+0x3e9bf11f
+// -0.869144
+0xbf5e8034
+// -0.169420
+0xbe2d7c8c
+// -0.378426
+0xbec1c108
+// 0.829828
+0x3f546f98
+// 0.628432
+0x3f20e0ef
+// -1.021615
+0xbf82c447
+// 1.440513
+0x3fb862be
+// 0.941566
+0x3f710a74
+// -1.745609
+0xbfdf7022
+// 1.314236
+0x3fa838e3
+// -0.329904
+0xbea8e91d
+// 1.612454
+0x3fce64e7
+// 0.469933
+0x3ef09b05
+// 0.211417
+0x3e587d95
+// -0.025598
+0xbcd1b3ee
+// 0.839153
+0x3f56d2c1
+// 0.057814
+0x3d6cced9
+// 0.788610
+0x3f49e260
+// -0.308370
+0xbe9de2b0
+// -0.230521
+0xbe6c0dd1
+// 1.174891
+0x3f9662d5
+// 0.932017
+0x3f6e98a3
+// 0.977687
+0x3f7a49af
+// -0.860455
+0xbf5c46c6
+// -0.510719
+0xbf02be74
+// -1.897351
+0xbff2dc69
+// 0.016532
+0x3c876e04
+// -0.612020
+0xbf1cad55
+// 0.441428
+0x3ee202d1
+// -1.470648
+0xbfbc3e31
+// 0.991979
+0x3f7df257
+// 1.956424
+0x3ffa6c18
+// 0.473413
+0x3ef2633e
+// -0.250552
+0xbe804855
+// -1.625874
+0xbfd01ca5
+// -0.155014
+0xbe1ebbff
+// 1.669532
+0x3fd5b33e
+// -0.025656
+0xbcd22d92
+// -0.068881
+0xbd8d115a
+// 0.163791
+0x3e27b8ce
+// 1.119094
+0x3f8f3e7c
+// -1.802363
+0xbfe6b3d6
+// -1.702842
+0xbfd9f6bc
+// 0.520641
+0x3f0548bc
+// -0.519046
+0xbf04e02c
+// 0.979492
+0x3f7ac002
+// -0.474060
+0xbef2b809
+// -0.191474
+0xbe4411c4
+// -1.714627
+0xbfdb78e6
+// -0.596864
+0xbf18cc16
+// 0.224422
+0x3e65ced8
+// -1.856051
+0xbfed9313
+// -0.219249
+0xbe6082b0
+// 0.329078
+0x3ea87cf5
+// -0.871314
+0xbf5f0e71
+// 0.646531
+0x3f258308
+// 0.925301
+0x3f6ce07f
+// -0.074134
+0xbd97d358
+// -0.019039
+0xbc9bf8b2
+// 1.013676
+0x3f81c01f
+// 0.796748
+0x3f4bf7b3
+// -1.001709
+0xbf8037fd
+// -0.033195
+0xbd07f70c
+// -0.151069
+0xbe1ab1bd
+// 1.019677
+0x3f8284c3
+// 0.436747
+0x3edf9d41
+// 0.023986
+0x3cc47d6f
+// -0.212774
+0xbe59e158
+// 0.072747
+0x3d94fc28
+// -0.830540
+0xbf549e48
+// -0.493261
+0xbefc8cc5
+// 1.120387
+0x3f8f68d9
+// -0.609724
+0xbf1c16d8
+// 1.163903
+0x3f94fac6
+// -0.387994
+0xbec6a71e
+// 0.250811
+0x3e806a5b
+// 0.322549
+0x3ea52529
+// 1.131973
+0x3f90e47d
+// 0.107626
+0x3ddc6b40
+// 2.599573
+0x40265f69
+// -0.429815
+0xbedc10b4
+// -1.013243
+0xbf81b1f2
+// 0.555349
+0x3f0e2b59
+// -1.283893
+0xbfa4569a
+// 1.614278
+0x3fcea0ad
+// -1.869262
+0xbfef43f9
+// -0.378907
+0xbec20018
+// -2.375443
+0xc0180743
+// -0.996230
+0xbf7f08ec
+// 0.702888
+0x3f33f070
+// 0.095130
+0x3dc2d3c5
+// 1.028568
+0x3f83a81d
+// 0.429293
+0x3edbcc3d
+// 0.605223
+0x3f1aefdd
+// -0.270594
+0xbe8a8b48
+// -0.060702
+0xbd78a28e
+// -1.745152
+0xbfdf6124
+// -0.818997
+0xbf51a9ca
+// -2.017297
+0xc0011b64
+// -0.800425
+0xbf4ce89f
+// 0.057744
+0x3d6c8493
+// -0.481656
+0xbef69b9f
+// -0.516920
+0xbf0454e7
+// 1.486539
+0x3fbe46ea
+// 1.925483
+0x3ff67637
+// -0.875782
+0xbf603348
+// -0.531133
+0xbf07f85a
+// 0.767948
+0x3f449835
+// -2.063007
+0xc004084e
+// 0.483269
+0x3ef76f07
+// -0.815555
+0xbf50c830
+// -0.666145
+0xbf2a8880

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/InputB8_f32.txt

@@ -1,242 +1,702 @@
 W
-120
-// 0.073031
-0x3d959128
-// 0.176650
-0x3e34e3c0
-// 0.064821
-0x3d84c0c4
-// 0.128546
-0x3e03a18d
-// 0.061577
-0x3d7c385b
-// 0.088410
-0x3db51034
-// 0.019936
-0x3ca3508e
-// 0.034320
-0x3d0c92d0
-// 0.191831
-0x3e446f5c
-// 0.048526
-0x3d46c38c
-// 0.081591
-0x3da718f6
-// 0.030762
-0x3cfc0062
-// 0.217147
-0x3e5e5bdd
-// 0.140998
-0x3e1061c3
-// 0.126726
-0x3e01c495
-// 0.025180
-0x3cce4592
-// 0.009365
-0x3c19709a
-// 0.076786
-0x3d9d41f2
-// 0.076342
-0x3d9c595f
-// 0.018410
-0x3c96d050
-// 0.130875
-0x3e060415
-// 0.041880
-0x3d2b8ada
-// 0.059024
-0x3d71c37d
-// 0.077266
-0x3d9e3d64
-// 0.049642
-0x3d4b5544
-// 0.076856
-0x3d9d66e1
-// 0.009913
-0x3c226bb7
-// 0.185438
-0x3e3de38d
-// 0.111185
-0x3de3b514
-// 0.083005
-0x3da9fe66
-// 0.104660
-0x3dd65820
-// 0.050109
-0x3d4d3f26
-// 0.039773
-0x3d22e92b
-// 0.061355
-0x3d7b4f68
-// 0.149725
-0x3e195195
-// 0.078337
-0x3da06f4b
-// 0.150706
-0x3e1a52b1
-// 0.055377
-0x3d62d2a5
-// 0.255748
-0x3e82f161
-// 0.011928
-0x3c436c0c
-// 0.063707
-0x3d827892
-// 0.099253
-0x3dcb454a
-// 0.001720
-0x3ae1650e
-// 0.018686
-0x3c991422
-// 0.057029
-0x3d69971b
-// 0.077400
-0x3d9e83fc
-// 0.052600
-0x3d57733f
-// 0.155847
-0x3e1f9652
-// 0.104162
-0x3dd552de
-// 0.143701
-0x3e132675
-// 0.016684
-0x3c88adb4
-// 0.021521
-0x3cb04c3d
-// 0.139378
-0x3e0eb8fb
-// 0.179808
-0x3e381f9d
-// 0.108843
-0x3ddee938
-// 0.018642
-0x3c98b668
-// 0.064157
-0x3d8364e2
-// 0.031151
-0x3cff30a1
-// 0.063106
-0x3d813ddc
-// 0.108846
-0x3ddeead3
-// 0.008963
-0x3c12d790
-// 0.054344
-0x3d5e982c
-// 0.133364
-0x3e08909a
-// 0.007249
-0x3bed8c99
-// 0.116270
-0x3dee1eb7
-// 0.137670
-0x3e0cf941
-// 0.082400
-0x3da8c14e
-// 0.074921
-0x3d99704d
-// 0.160275
-0x3e241f14
-// 0.094023
-0x3dc08f38
-// 0.055244
-0x3d6247ad
-// 0.075277
-0x3d9a2af1
-// 0.003395
-0x3b5e7ef2
-// 0.078291
-0x3da056de
-// 0.028401
-0x3ce8a9e2
-// 0.020805
-0x3caa6f47
-// 0.124209
-0x3dfe612a
-// 0.161146
-0x3e25038e
-// 0.181382
-0x3e39bc45
-// 0.141190
-0x3e109421
-// 0.027261
-0x3cdf52ed
-// 0.125799
-0x3e00d163
-// 0.083640
-0x3dab4b6f
-// 0.024481
-0x3cc88b77
-// 0.140041
-0x3e0f66d1
-// 0.033849
-0x3d0aa58e
-// 0.147684
-0x3e173a78
-// 0.049306
-0x3d49f490
-// 0.073572
-0x3d96accc
-// 0.025476
-0x3cd0b369
-// 0.147370
-0x3e16e849
-// 0.013977
-0x3c64ff3d
+350
+// 0.074465
+0x3d988126
+// 0.062631
+0x3d8044c9
+// 0.012207
+0x3c480117
+// 0.016485
+0x3c870b71
+// 0.012380
+0x3c4ad687
+// 0.010502
+0x3c2c11a8
+// 0.069556
+0x3d8e7324
+// 0.033063
+0x3d076c9b
+// 0.049775
+0x3d4be093
+// 0.040194
+0x3d24a220
+// 0.019834
+0x3ca27abb
+// 0.030833
+0x3cfc963e
+// 0.040073
+0x3d242315
+// 0.052188
+0x3d55c34d
+// 0.014333
+0x3c6ad365
+// 0.084720
+0x3dad8190
+// 0.064739
+0x3d8495a7
+// 0.004754
+0x3b9bc706
+// 0.036976
+0x3d17744c
+// 0.005567
+0x3bb66cd0
+// 0.004991
+0x3ba38d19
+// 0.004241
+0x3b8afa13
+// 0.023539
+0x3cc0d5c6
+// 0.019130
+0x3c9cb75e
+// 0.008761
+0x3c0f89de
+// 0.001400
+0x3ab7758b
+// 0.012173
+0x3c477151
+// 0.045834
+0x3d3bbcd7
+// 0.025423
+0x3cd0434e
+// 0.053914
+0x3d5cd4ef
+// 0.026439
+0x3cd896c1
+// 0.004457
+0x3b9207e8
+// 0.006031
+0x3bc59d85
+// 0.024667
+0x3cca12ff
+// 0.003726
+0x3b742aaf
+// 0.006183
+0x3bca9ae5
+// 0.047506
+0x3d4295b7
+// 0.038432
+0x3d1d6ab2
+// 0.085140
+0x3dae5e00
+// 0.014449
+0x3c6cbc51
+// 0.006132
+0x3bc8f2fa
+// 0.002129
+0x3b0b896f
+// 0.025757
+0x3cd300db
+// 0.030793
+0x3cfc4122
+// 0.026100
+0x3cd5d07a
+// 0.046471
+0x3d3e5817
+// 0.008614
+0x3c0d2316
+// 0.025788
+0x3cd34166
+// 0.048028
+0x3d44b8ef
+// 0.012848
+0x3c527f62
+// 0.032751
+0x3d062651
+// 0.004946
+0x3ba21386
+// 0.010436
+0x3c2afb3c
+// 0.091558
+0x3dbb8295
+// 0.005118
+0x3ba7b610
+// 0.063944
+0x3d82f546
+// 0.037347
+0x3d18f983
+// 0.010599
+0x3c2da8e4
+// 0.011138
+0x3c367ad6
+// 0.001808
+0x3aecf7fb
+// 0.001621
+0x3ad46bc4
+// 0.008850
+0x3c11018b
+// 0.037748
+0x3d1a9de3
+// 0.031528
+0x3d0123d3
+// 0.026312
+0x3cd78cb5
+// 0.107044
+0x3ddb39a3
+// 0.002750
+0x3b344032
+// 0.002245
+0x3b132854
+// 0.039603
+0x3d2236d4
+// 0.048281
+0x3d45c1ee
+// 0.020023
+0x3ca40657
+// 0.027927
+0x3ce4c6cb
+// 0.079615
+0x3da30d07
+// 0.014111
+0x3c67303b
+// 0.028880
+0x3cec953b
+// 0.015009
+0x3c75e6fc
+// 0.085485
+0x3daf12e9
+// 0.000692
+0x3a35631d
+// 0.002477
+0x3b224fe1
+// 0.034737
+0x3d0e485f
+// 0.017889
+0x3c928bd6
+// 0.054034
+0x3d5d52e5
+// 0.021914
+0x3cb38548
+// 0.006345
+0x3bcfed2e
+// 0.020925
+0x3cab6a0d
+// 0.023520
+0x3cc0ac8a
+// 0.032886
+0x3d06b3b9
+// 0.037624
+0x3d1a1ba4
+// 0.058445
+0x3d6f6484
+// 0.057812
+0x3d6ccbe5
+// 0.020958
+0x3cabb02f
+// 0.020349
+0x3ca6b210
+// 0.005412
+0x3bb15324
+// 0.018054
+0x3c93e558
+// 0.021892
+0x3cb355d9
+// 0.030601
+0x3cfaaedf
+// 0.039901
+0x3d236fa7
+// 0.000668
+0x3a2f28db
+// 0.006598
+0x3bd837f0
+// 0.038036
+0x3d1bcb39
+// 0.067670
+0x3d8a9660
+// 0.049339
+0x3d4a17cd
+// 0.034068
+0x3d0b8ab9
+// 0.003635
+0x3b6e39c4
+// 0.002472
+0x3b2201e2
+// 0.005194
+0x3baa30f2
+// 0.025287
+0x3ccf25d4
+// 0.000813
+0x3a553e3b
+// 0.033280
+0x3d085082
+// 0.007522
+0x3bf67c68
+// 0.013306
+0x3c5a02c4
+// 0.022835
+0x3cbb0fc0
+// 0.050022
+0x3d4ce39b
+// 0.027191
+0x3cdebf85
+// 0.026414
+0x3cd862fe
+// 0.021372
+0x3caf1433
+// 0.054618
+0x3d5fb6ba
+// 0.024746
+0x3ccab86b
+// 0.005457
+0x3bb2d3e6
+// 0.009456
+0x3c1aeb4c
+// 0.010459
+0x3c2b5d6f
+// 0.018345
+0x3c96479e
+// 0.049490
+0x3d4ab608
+// 0.004234
+0x3b8ac102
+// 0.042290
+0x3d2d389b
+// 0.061023
+0x3d79f2d3
+// 0.038073
+0x3d1bf248
+// 0.077639
+0x3d9f0107
+// 0.035487
+0x3d115a6b
+// 0.013975
+0x3c64f82b
+// 0.002077
+0x3b082525
+// 0.027237
+0x3cdf2027
+// 0.036658
+0x3d162715
+// 0.001405
+0x3ab8257b
+// 0.024084
+0x3cc54b07
+// 0.046724
+0x3d3f6189
+// 0.023174
+0x3cbdd6d9
+// 0.052315
+0x3d564870
+// 0.038389
+0x3d1d3e2a
+// 0.069409
+0x3d8e2672
+// 0.010633
+0x3c2e34fd
+// 0.032497
+0x3d051b8a
+// 0.073968
+0x3d977c63
+// 0.058135
+0x3d6e1f2d
+// 0.099899
+0x3dcc9814
+// 0.008125
+0x3c051d6b
+// 0.026365
+0x3cd7fbda
+// 0.001519
+0x3ac72533
+// 0.001293
+0x3aa97720
+// 0.026030
+0x3cd53be3
+// 0.001963
+0x3b00a401
+// 0.083194
+0x3daa61bf
+// 0.041257
+0x3d28fd65
+// 0.004513
+0x3b93e4ff
+// 0.007365
+0x3bf15392
+// 0.017520
+0x3c8f8528
+// 0.037602
+0x3d1a050a
+// 0.035704
+0x3d123e17
+// 0.037329
+0x3d18e62b
+// 0.014399
+0x3c6be8fc
+// 0.036239
+0x3d146f11
+// 0.000967
+0x3a7d8dd5
+// 0.036917
+0x3d1735da
+// 0.049628
+0x3d4b46b2
+// 0.022263
+0x3cb66104
+// 0.023858
+0x3cc372c0
+// 0.029653
+0x3cf2eb24
+// 0.019390
+0x3c9ed848
+// 0.045362
+0x3d39cd8b
+// 0.003695
+0x3b722677
+// 0.009396
+0x3c19f0a0
+// 0.013913
+0x3c63f14b
+// 0.031497
+0x3d01032d
+// 0.025720
+0x3cd2b316
+// 0.032192
+0x3d03dc19
+// 0.005433
+0x3bb2038f
+// 0.008506
+0x3c0b5eab
+// 0.021258
+0x3cae24b2
+// 0.059523
+0x3d73cebb
+// 0.003405
+0x3b5f2104
+// 0.051977
+0x3d54e65b
+// 0.034455
+0x3d0d2083
+// 0.010746
+0x3c301100
+// 0.029566
+0x3cf23367
+// 0.043845
+0x3d3396aa
+// 0.040302
+0x3d2513eb
+// 0.002321
+0x3b181950
+// 0.016603
+0x3c8802c7
+// 0.001620
+0x3ad464b3
+// 0.015534
+0x3c7e8093
+// 0.026791
+0x3cdb7832
+// 0.056229
+0x3d664fe6
+// 0.056769
+0x3d688705
+// 0.007897
+0x3c0161f7
+// 0.001931
+0x3afd1558
+// 0.036348
+0x3d14e142
+// 0.007387
+0x3bf210de
+// 0.010354
+0x3c29a2c9
+// 0.066053
+0x3d874691
+// 0.073260
+0x3d960947
+// 0.037106
+0x3d17fc69
+// 0.056121
+0x3d65df3d
+// 0.088871
+0x3db60210
+// 0.013427
+0x3c5bfeee
+// 0.022329
+0x3cb6eb5a
+// 0.020211
+0x3ca59279
+// 0.023217
+0x3cbe31e5
+// 0.018135
+0x3c948f1a
+// 0.002368
+0x3b1b3014
+// 0.030103
+0x3cf69a7f
+// 0.027653
+0x3ce288eb
+// 0.052063
+0x3d553fbb
+// 0.007614
+0x3bf9825c
+// 0.023886
+0x3cc3acd4
+// 0.006375
+0x3bd0e14e
+// 0.041487
+0x3d29ee4b
+// 0.040043
+0x3d240448
+// 0.041836
+0x3d2b5c13
+// 0.016600
+0x3c87fc56
+// 0.009465
+0x3c1b14fd
+// 0.031795
+0x3d023be3
+// 0.021645
+0x3cb1517e
+// 0.038660
+0x3d1e5a26
+// 0.047672
+0x3d43442e
+// 0.049012
+0x3d48c04e
+// 0.002552
+0x3b2739e1
+// 0.024673
+0x3cca1e04
+// 0.030914
+0x3cfd3f21
+// 0.056962
+0x3d695115
+// 0.014927
+0x3c748f5d
+// 0.000848
+0x3a5e3960
+// 0.035904
+0x3d130fac
+// 0.024516
+0x3cc8d541
+// 0.055777
+0x3d647635
+// 0.002988
+0x3b43cd39
+// 0.043795
+0x3d336295
+// 0.022459
+0x3cb7fc28
+// 0.012302
+0x3c498da0
+// 0.035105
+0x3d0fca3b
+// 0.006843
+0x3be03abf
+// 0.015285
+0x3c7a6ccf
+// 0.033517
+0x3d09491c
+// 0.025383
+0x3ccfef17
+// 0.041263
+0x3d2903bc
+// 0.058183
+0x3d6e510b
+// 0.033542
+0x3d096302
+// 0.062184
+0x3d7eb50e
+// 0.046817
+0x3d3fc3a4
+// 0.011752
+0x3c408c87
+// 0.057441
+0x3d6b4736
+// 0.016741
+0x3c89237f
+// 0.007531
+0x3bf6c99a
+// 0.000912
+0x3a6f0cc6
+// 0.029893
+0x3cf4e30b
+// 0.002060
+0x3b06f962
+// 0.028093
+0x3ce6231d
+// 0.010985
+0x3c33fb1e
+// 0.008212
+0x3c068b5c
+// 0.041854
+0x3d2b6e95
+// 0.033202
+0x3d07fe4f
+// 0.034828
+0x3d0ea844
+// 0.030652
+0x3cfb1a6e
+// 0.018193
+0x3c950a82
+// 0.067590
+0x3d8a6c97
+// 0.000589
+0x3a1a61f1
+// 0.021802
+0x3cb29a78
+// 0.015725
+0x3c80d1f6
+// 0.052389
+0x3d569636
+// 0.035338
+0x3d10be23
+// 0.069694
+0x3d8ebbe1
+// 0.016865
+0x3c8a2787
+// 0.008925
+0x3c123c34
+// 0.057919
+0x3d6d3c7e
+// 0.005522
+0x3bb4f2d6
+// 0.059474
+0x3d739b4b
+// 0.000914
+0x3a6f9770
+// 0.002454
+0x3b20cf45
+// 0.005835
+0x3bbf31a2
+// 0.039866
+0x3d234a5e
+// 0.064206
+0x3d837e82
+// 0.078092
+0x3d9fee92
+// 0.023876
+0x3cc3987b
+// 0.023803
+0x3cc2ff09
+// 0.044919
+0x3d37fd2c
+// 0.021740
+0x3cb21898
+// 0.008781
+0x3c0fdde7
+// 0.078632
+0x3da109eb
+// 0.027372
+0x3ce03b35
+// 0.010292
+0x3c289f65
+// 0.085118
+0x3dae5245
+// 0.010055
+0x3c24bc4f
+// 0.015091
+0x3c774200
+// 0.039958
+0x3d23ab2c
+// 0.029650
+0x3cf2e3de
+// 0.042434
+0x3d2dcf3c
+// 0.003400
+0x3b5ece2c
+// 0.000873
+0x3a64e3b7
+// 0.046487
+0x3d3e68f5
+// 0.036539
+0x3d15a981
+// 0.045938
+0x3d3c297f
+// 0.001522
+0x3ac787a6
+// 0.006928
+0x3be303e8
+// 0.046762
+0x3d3f8987
+// 0.020029
+0x3ca413f6
+// 0.001100
+0x3a902ce7
+// 0.009758
+0x3c1fdee0
+// 0.003336
+0x3b5aa305
+// 0.038088
+0x3d1c0276
+// 0.022621
+0x3cb94f42
+// 0.051381
+0x3d52746f
+// 0.027962
+0x3ce50ff6
+// 0.053376
+0x3d5aa0ff
+// 0.017793
+0x3c91c32c
+// 0.011502
+0x3c3c7369
+// 0.014792
+0x3c725a1c
+// 0.033689
+0x3d09fd16
+// 0.003203
+0x3b51ea92
+// 0.077366
+0x3d9e71fe
+// 0.012792
+0x3c519457
+// 0.030155
+0x3cf707d8
+// 0.016528
+0x3c87652a
+// 0.038210
+0x3d1c81ff
+// 0.048043
+0x3d44c839
 // 0.055631
-0x3d63dd3d
-// 0.065558
-0x3d864375
-// 0.176722
-0x3e34f6a0
-// 0.070814
-0x3d9106ea
-// 0.018844
-0x3c9a5fbc
-// 0.076750
-0x3d9d2f3d
-// 0.065185
-0x3d857fc5
-// 0.156068
-0x3e1fd03d
-// 0.100892
-0x3dcea073
-// 0.104545
-0x3dd61b83
-// 0.007781
-0x3bfef3f0
-// 0.110860
-0x3de30a94
-// 0.064030
-0x3d8321f2
-// 0.070530
-0x3d9071ec
-// 0.140259
-0x3e0f9fef
-// 0.084257
-0x3dac8f0f
-// 0.044459
-0x3d361af9
-// 0.165073
-0x3e2908f5
-// 0.020206
-0x3ca5870c
-// 0.037108
-0x3d17feb6
-// 0.103671
-0x3dd45188
-// 0.170111
-0x3e2e318e
-// 0.046444
-0x3d3e3c61
-// 0.117384
-0x3df066c7
-// 0.098929
-0x3dca9b46
-// 0.103931
-0x3dd4d9f5
-// 0.001287
-0x3aa8b54a
-// 0.091396
-0x3dbb2dd0
+0x3d63dd68
+// 0.011277
+0x3c38c1ac
+// 0.070696
+0x3d90c8d0
+// 0.029649
+0x3cf2e200
+// 0.020919
+0x3cab5d89
+// 0.002831
+0x3b398b43
+// 0.030611
+0x3cfac453
+// 0.012776
+0x3c515323
+// 0.018012
+0x3c938df0
+// 0.008053
+0x3c03f151
+// 0.001807
+0x3aecc9b2
+// 0.051937
+0x3d54bc5a
+// 0.024374
+0x3cc7ac4f
+// 0.060037
+0x3d75e915
+// 0.023821
+0x3cc32524
+// 0.001719
+0x3ae13f86
+// 0.014335
+0x3c6adb7d
+// 0.015384
+0x3c7c0d6f
+// 0.044241
+0x3d3535e8
+// 0.057304
+0x3d6ab7de
+// 0.026064
+0x3cd5847a
+// 0.015807
+0x3c817dc8
+// 0.022855
+0x3cbb3a24
+// 0.061397
+0x3d7b7b8a
+// 0.014383
+0x3c6ba4d3
+// 0.024272
+0x3cc6d575
+// 0.019825
+0x3ca26855

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref1_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 1.050994
-0x3f8686fa
-// 0.770592
-0x3f454585
-// 1.367209
-0x3faf00b2
-// 1.890327
-0x3ff1f63e
-// 0.985315
-0x3f7c3d9c
-// 0.948532
-0x3f72d302
-// 1.586398
-0x3fcb0f1a
-// 0.561266
-0x3f0faf1e
-// 1.006152
-0x3f80c998
-// 1.058311
-0x3f8776bb
+// 0.943085
+0x3f716e01
+// 1.130403
+0x3f90b109
+// 1.205219
+0x3f9a44a2
+// 1.063779
+0x3f8829e7
+// 1.192873
+0x3f98b00e
+// 0.713279
+0x3f369977
+// 0.939387
+0x3f707ba7
+// 1.010824
+0x3f8162ad
+// 0.846457
+0x3f58b163
+// 0.766557
+0x3f443d19

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref2_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 7.876377
-0x40fc0b49
-// 6.952287
-0x40de7923
-// 9.756665
-0x411c1b4d
-// 9.818140
-0x411d171a
-// 8.394031
-0x41064df4
-// 8.528627
-0x41087542
-// 9.376871
-0x411607aa
-// 6.656672
-0x40d50375
-// 8.246555
-0x4103f1e3
-// 9.699050
-0x411b2f4f
+// 25.260820
+0x41ca1629
+// 26.700724
+0x41d59b15
+// 27.035882
+0x41d8497d
+// 24.170678
+0x41c15d8c
+// 28.632569
+0x41e50f81
+// 23.848359
+0x41bec970
+// 23.611153
+0x41bce3a4
+// 27.138383
+0x41d91b68
+// 25.060365
+0x41c87ba1
+// 24.291245
+0x41c25478

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref3_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 3.674277
-0x406b275c
-// 2.128956
-0x400840d2
-// 2.604517
-0x4026b06a
-// 4.807487
-0x4099d6ef
-// 3.972849
-0x407e432a
-// 2.011099
-0x4000b5d8
-// 2.821669
-0x4034963b
-// 1.710022
-0x3fdae203
-// 3.370791
-0x4057bb0c
-// 2.637786
-0x4028d17b
+// 3.210621
+0x404d7ad0
+// 4.698527
+0x40965a54
+// 3.387568
+0x4058cdea
+// 3.159346
+0x404a32ba
+// 3.393280
+0x40592b81
+// 2.479391
+0x401eae57
+// 2.824532
+0x4034c523
+// 3.078885
+0x40450c73
+// 2.972730
+0x403e4135
+// 2.722015
+0x402e357f

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref4_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 14.122970
-0x4161f7b0
-// 8.388757
-0x41063859
-// 13.934073
-0x415ef1f6
-// 18.788568
-0x41964efd
-// 14.866911
-0x416ddede
-// 12.512610
-0x414833a7
-// 14.262105
-0x41643195
-// 8.109187
-0x4101bf3b
-// 13.187713
-0x415300e0
-// 14.818801
-0x416d19cf
+// 42.884044
+0x422b8943
+// 42.707574
+0x422ad48e
+// 47.985164
+0x423ff0cf
+// 35.063801
+0x420c4155
+// 51.956146
+0x424fd318
+// 28.303201
+0x41e26cf5
+// 32.501327
+0x4202015c
+// 41.998421
+0x4227fe62
+// 38.091147
+0x42185d56
+// 36.294160
+0x42112d38

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref5_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 1.042156
-0x3f85655d
-// 0.728789
-0x3f3a91f0
-// 1.147441
-0x3f92df5b
-// 1.532731
-0x3fc43088
-// 1.110376
-0x3f8e20d0
-// 0.950113
-0x3f733aa3
-// 1.290222
-0x3fa52601
-// 0.517924
-0x3f0496a5
-// 1.044841
-0x3f85bd5c
-// 1.037092
-0x3f84bf6c
+// 0.872900
+0x3f5f765b
+// 1.059186
+0x3f879367
+// 1.198025
+0x3f9958e0
+// 1.142244
+0x3f92350e
+// 1.124414
+0x3f8fecca
+// 0.694060
+0x3f31ade9
+// 0.934941
+0x3f6f5852
+// 0.983742
+0x3f7bd683
+// 0.818550
+0x3f518c79
+// 0.711705
+0x3f363254

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref6_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 1.168452
-0x3f958fd3
-// 0.796504
-0x3f4be7a9
-// 1.165600
-0x3f953263
-// 1.631461
-0x3fd0d3b9
-// 1.103752
-0x3f8d47c0
-// 0.977194
-0x3f7a2964
-// 1.296039
-0x3fa5e499
-// 0.541990
-0x3f0abfd6
-// 1.026969
-0x3f8373b4
-// 1.035382
-0x3f848764
+// 0.870512
+0x3f5ed9dd
+// 1.119789
+0x3f8f553c
+// 1.185343
+0x3f97b951
+// 1.111726
+0x3f8e4d07
+// 1.124337
+0x3f8fea49
+// 0.705384
+0x3f349406
+// 0.945177
+0x3f71f717
+// 1.010589
+0x3f815afa
+// 0.835368
+0x3f55daa6
+// 0.701478
+0x3f33940a

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref7_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 5.289160
-0x40a940cc
-// 3.412243
-0x405a6230
-// 4.611134
-0x40938e69
-// 7.107662
-0x40e371f8
-// 5.664012
-0x40b53f97
-// 4.236576
-0x40879207
-// 5.007020
-0x40a03983
-// 2.942135
-0x403c4bf3
-// 4.840440
-0x409ae4e2
-// 5.095986
-0x40a31252
+// 8.671314
+0x410abdb3
+// 9.626203
+0x411a04ee
+// 9.703563
+0x411b41cb
+// 7.581915
+0x40f29f0c
+// 10.361117
+0x4125c723
+// 6.385656
+0x40cc574b
+// 6.817382
+0x40da27fe
+// 8.416707
+0x4106aad4
+// 7.811620
+0x40f9f8ca
+// 7.340256
+0x40eae360

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref8_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.290537
-0x3e94c137
-// 0.277200
-0x3e8ded1c
-// 0.339279
-0x3eadb5f6
-// 0.378618
-0x3ec1da33
-// 0.384567
-0x3ec4e5f9
-// 0.365455
-0x3ebb1cf2
-// 0.280450
-0x3e8f972a
-// 0.380094
-0x3ec29ba8
-// 0.268470
-0x3e8974dc
-// 0.381263
-0x3ec334e3
+// 0.381567
+0x3ec35cb3
+// 0.378719
+0x3ec1e772
+// 0.364423
+0x3eba95b0
+// 0.318695
+0x3ea32bf3
+// 0.415774
+0x3ed4e05c
+// 0.349131
+0x3eb2c155
+// 0.327241
+0x3ea78c2b
+// 0.406309
+0x3ed007ca
+// 0.383680
+0x3ec471b3
+// 0.414107
+0x3ed405e1

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceF32/Ref9_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 4.187354
-0x4085fece
-// 2.516821
-0x40211399
-// 4.611134
-0x40938e69
-// 5.160622
-0x40a523d0
-// 4.150105
-0x4084cda9
-// 3.075515
-0x4044d53c
-// 3.300479
-0x40533b0b
-// 2.942135
-0x403c4bf3
-// 3.815488
-0x407430f5
-// 3.290184
-0x40529260
+// 4.411771
+0x408d2d3a
+// 9.626203
+0x411a04ee
+// 9.703563
+0x411b41cb
+// 7.581915
+0x40f29f0c
+// 10.361117
+0x4125c723
+// 4.202011
+0x408676df
+// 6.817382
+0x40da27fe
+// 4.281130
+0x4088ff03
+// 4.947443
+0x409e5174
+// 4.601837
+0x40934240

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Dims1_s16.txt

@@ -2,7 +2,7 @@ H
 3
 // 10
 0x000A
-// 12
-0x000C
-// 1
-0x0001
+// 35
+0x0023
+// 2
+0x0002

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/InputA1_u32.txt

@@ -1,22 +1,42 @@
 W
-10
-// 0x43000000
-0x43000000
-// 0xC8E00000
-0xC8E00000
-// 0x6C700000
-0x6C700000
-// 0xF8200000
-0xF8200000
-// 0x38D00000
-0x38D00000
-// 0xD8F00000
-0xD8F00000
-// 0x4B300000
-0x4B300000
-// 0x90E00000
-0x90E00000
-// 0x69400000
-0x69400000
-// 0xFEC00000
-0xFEC00000
+20
+// 0x13E7E558
+0x13E7E558
+// 0x00000000
+0x00000000
+// 0x086CFFA1
+0x086CFFA1
+// 0x60000000
+0x60000000
+// 0x2DF5A439
+0x2DF5A439
+// 0xE0000000
+0xE0000000
+// 0xE7FD0F25
+0xE7FD0F25
+// 0xA0000000
+0xA0000000
+// 0xE3E73F09
+0xE3E73F09
+// 0x00000000
+0x00000000
+// 0xD93D9805
+0xD93D9805
+// 0x20000000
+0x20000000
+// 0x055636FF
+0x055636FF
+// 0x20000000
+0x20000000
+// 0x140A2D40
+0x140A2D40
+// 0x60000000
+0x60000000
+// 0x9CB310A4
+0x9CB310A4
+// 0xC0000000
+0xC0000000
+// 0x13CBB13A
+0x13CBB13A
+// 0xA0000000
+0xA0000000

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/InputB1_u32.txt

@@ -1,22 +1,42 @@
 W
-10
-// 0x46D00000
-0x46D00000
-// 0xA1200000
-0xA1200000
-// 0xAB400000
-0xAB400000
-// 0xDDD00000
-0xDDD00000
-// 0xDF000000
-0xDF000000
-// 0x37400000
-0x37400000
-// 0xC0F00000
-0xC0F00000
-// 0x03E00000
-0x03E00000
-// 0xEF500000
-0xEF500000
-// 0x67100000
-0x67100000
+20
+// 0xC5236528
+0xC5236528
+// 0xE0000000
+0xE0000000
+// 0x9337079D
+0x9337079D
+// 0x60000000
+0x60000000
+// 0x6C53C4E9
+0x6C53C4E9
+// 0xA0000000
+0xA0000000
+// 0x9E9D8D44
+0x9E9D8D44
+// 0xA0000000
+0xA0000000
+// 0xCDC9D940
+0xCDC9D940
+// 0x40000000
+0x40000000
+// 0x475E61D3
+0x475E61D3
+// 0xC0000000
+0xC0000000
+// 0xDBA423A5
+0xDBA423A5
+// 0xC0000000
+0xC0000000
+// 0xE5E5FCD6
+0xE5E5FCD6
+// 0x60000000
+0x60000000
+// 0xFA83CBDD
+0xFA83CBDD
+// 0x60000000
+0x60000000
+// 0xDDB01AFB
+0xDDB01AFB
+// 0x00000000
+0x00000000

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref1_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.555556
-0x3f0e38e4
-// 0.600000
-0x3f19999a
-// 0.538462
-0x3f09d89e
-// 0.466667
-0x3eeeeeef
-// 0.692308
-0x3f313b14
-// 0.714286
-0x3f36db6e
-// 0.500000
-0x3f000000
-// 0.400000
-0x3ecccccd
-// 0.285714
-0x3e924925
-// 0.466667
-0x3eeeeeef
+// 0.454545
+0x3ee8ba2f
+// 0.513514
+0x3f03759f
+// 0.315789
+0x3ea1af28
+// 0.300000
+0x3e99999a
+// 0.485714
+0x3ef8af8b
+// 0.657143
+0x3f283a84
+// 0.567568
+0x3f114c1c
+// 0.588235
+0x3f169697
+// 0.513514
+0x3f03759f
+// 0.567568
+0x3f114c1c

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref2_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.416667
-0x3ed55555
-// 0.500000
-0x3f000000
-// 0.583333
-0x3f155555
-// 0.583333
-0x3f155555
-// 0.750000
-0x3f400000
-// 0.833333
-0x3f555555
-// 0.500000
-0x3f000000
-// 0.333333
-0x3eaaaaab
-// 0.333333
-0x3eaaaaab
-// 0.583333
-0x3f155555
+// 0.428571
+0x3edb6db7
+// 0.542857
+0x3f0af8b0
+// 0.342857
+0x3eaf8af9
+// 0.342857
+0x3eaf8af9
+// 0.485714
+0x3ef8af8b
+// 0.657143
+0x3f283a84
+// 0.600000
+0x3f19999a
+// 0.571429
+0x3f124925
+// 0.542857
+0x3f0af8b0
+// 0.600000
+0x3f19999a

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref3_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.714286
-0x3f36db6e
-// 0.750000
-0x3f400000
-// 0.700000
-0x3f333333
-// 0.636364
-0x3f22e8ba
-// 0.818182
-0x3f51745d
-// 0.833333
-0x3f555555
-// 0.666667
-0x3f2aaaab
-// 0.571429
-0x3f124925
-// 0.444444
-0x3ee38e39
-// 0.636364
-0x3f22e8ba
+// 0.625000
+0x3f200000
+// 0.678571
+0x3f2db6db
+// 0.480000
+0x3ef5c28f
+// 0.461538
+0x3eec4ec5
+// 0.653846
+0x3f276276
+// 0.793103
+0x3f4b08d4
+// 0.724138
+0x3f39611a
+// 0.740741
+0x3f3da12f
+// 0.678571
+0x3f2db6db
+// 0.724138
+0x3f39611a

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref4_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.882353
-0x3f61e1e2
-// 0.888889
-0x3f638e39
-// 0.842105
-0x3f579436
-// 0.789474
-0x3f4a1af3
-// 0.904762
-0x3f679e7a
-// 0.909091
-0x3f68ba2f
+// 0.820000
+0x3f51eb85
 // 0.833333
 0x3f555555
-// 0.812500
-0x3f500000
-// 0.687500
-0x3f300000
-// 0.789474
-0x3f4a1af3
+// 0.723404
+0x3f393105
+// 0.702128
+0x3f33bea3
+// 0.826923
+0x3f53b13b
+// 0.896552
+0x3f65846a
+// 0.857143
+0x3f5b6db7
+// 0.872727
+0x3f5f6b0e
+// 0.833333
+0x3f555555
+// 0.857143
+0x3f5b6db7

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref5_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.588235
-0x3f169697
-// 0.666667
-0x3f2aaaab
-// 0.736842
-0x3f3ca1af
-// 0.736842
-0x3f3ca1af
-// 0.857143
-0x3f5b6db7
-// 0.909091
-0x3f68ba2f
-// 0.666667
-0x3f2aaaab
-// 0.500000
-0x3f000000
-// 0.500000
-0x3f000000
-// 0.736842
-0x3f3ca1af
+// 0.600000
+0x3f19999a
+// 0.703704
+0x3f3425ed
+// 0.510638
+0x3f02b931
+// 0.510638
+0x3f02b931
+// 0.653846
+0x3f276276
+// 0.793103
+0x3f4b08d4
+// 0.750000
+0x3f400000
+// 0.727273
+0x3f3a2e8c
+// 0.703704
+0x3f3425ed
+// 0.750000
+0x3f400000

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref6_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.833333
-0x3f555555
-// 0.833333
-0x3f555555
-// 0.750000
-0x3f400000
-// 0.666667
-0x3f2aaaab
-// 0.833333
-0x3f555555
-// 0.833333
-0x3f555555
-// 0.750000
-0x3f400000
-// 0.750000
-0x3f400000
-// 0.583333
-0x3f155555
-// 0.666667
-0x3f2aaaab
+// 0.742857
+0x3f3e2be3
+// 0.742857
+0x3f3e2be3
+// 0.628571
+0x3f20ea0f
+// 0.600000
+0x3f19999a
+// 0.742857
+0x3f3e2be3
+// 0.828571
+0x3f541d42
+// 0.771429
+0x3f457c58
+// 0.800000
+0x3f4ccccd
+// 0.742857
+0x3f3e2be3
+// 0.771429
+0x3f457c58

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref7_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.588235
-0x3f169697
-// 0.666667
-0x3f2aaaab
-// 0.736842
-0x3f3ca1af
-// 0.736842
-0x3f3ca1af
-// 0.857143
-0x3f5b6db7
-// 0.909091
-0x3f68ba2f
-// 0.666667
-0x3f2aaaab
-// 0.500000
-0x3f000000
-// 0.500000
-0x3f000000
-// 0.736842
-0x3f3ca1af
+// 0.600000
+0x3f19999a
+// 0.703704
+0x3f3425ed
+// 0.510638
+0x3f02b931
+// 0.510638
+0x3f02b931
+// 0.653846
+0x3f276276
+// 0.793103
+0x3f4b08d4
+// 0.750000
+0x3f400000
+// 0.727273
+0x3f3a2e8c
+// 0.703704
+0x3f3425ed
+// 0.750000
+0x3f400000

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref8_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.833333
-0x3f555555
-// 0.857143
-0x3f5b6db7
-// 0.823529
-0x3f52d2d3
-// 0.777778
-0x3f471c72
-// 0.900000
-0x3f666666
-// 0.909091
-0x3f68ba2f
-// 0.800000
-0x3f4ccccd
-// 0.727273
-0x3f3a2e8c
-// 0.615385
-0x3f1d89d9
-// 0.777778
-0x3f471c72
+// 0.769231
+0x3f44ec4f
+// 0.808511
+0x3f4efa8e
+// 0.648649
+0x3f260dd6
+// 0.631579
+0x3f21af28
+// 0.790698
+0x3f4a6b2a
+// 0.884615
+0x3f627627
+// 0.840000
+0x3f570a3d
+// 0.851064
+0x3f59df52
+// 0.808511
+0x3f4efa8e
+// 0.840000
+0x3f570a3d

CMSIS/DSP/Testing/Patterns/DSP/Distance/DistanceU32/Ref9_f32.txt

@@ -1,22 +1,22 @@
 W
 10
-// 0.571429
-0x3f124925
-// 1.000000
-0x3f800000
-// 1.333333
-0x3faaaaab
-// 1.428571
-0x3fb6db6e
-// 1.818182
-0x3fe8ba2f
-// 2.000000
-0x40000000
-// 1.000000
-0x3f800000
-// 0.421053
-0x3ed79436
-// 0.000000
-0x0
-// 1.428571
-0x3fb6db6e
+// 0.722581
+0x3f38fb0c
+// 1.176471
+0x3f969697
+// 0.424242
+0x3ed9364e
+// 0.405063
+0x3ecf6475
+// 0.927152
+0x3f6d59db
+// 1.566265
+0x3fc87b60
+// 1.392405
+0x3fb23a54
+// 1.066667
+0x3f888889
+// 1.106383
+0x3f8d9df5
+// 1.392405
+0x3fb23a54

CMSIS/DoxyGen/DSP/dsp.dxy

@@ -38,7 +38,7 @@ PROJECT_NAME           = CMSIS-DSP
 # could be handy for archiving the generated documentation or if some version
 # control system is used.
 
-PROJECT_NUMBER         = "Version 1.7.0"
+PROJECT_NUMBER         = "Version 1.8.0"
 
 # Using the PROJECT_BRIEF tag one can provide an optional one line description
 # for a project that appears at the top of each page and should give viewer a
@@ -820,7 +820,8 @@ RECURSIVE              = YES
 # run.
 
 EXCLUDE                = math_helper.* \
-                         ../../DSP/Source/DistanceFunctions/arm_boolean_distance_template.h
+                         ../../DSP/Source/DistanceFunctions/arm_boolean_distance_template.h \
+                         ../../DSP/Source/DistanceFunctions/arm_boolean_distance.c
 
 # The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
 # directories that are symbolic links (a Unix file system feature) are excluded

CMSIS/DoxyGen/DSP/src/history.txt

@@ -6,6 +6,38 @@
     <th>Version</th>
     <th>Description</th>
   </tr>
+  <tr>
+    <td>V1.8.0</td>
+    <td> 
+      - New folder SVMFunctions : Support vector machines.
+      Training must be done with scikit-learn. 
+      The python script DSP/Testing/PatternGenerations/SVM.py is showing how
+      to generate parameters for CMSIS-DSP from the corresponding trained python object.
+
+      - New folder BayesFunctions : Functions related to Bayesian probability
+      In this version only a naive gaussian classifier.
+      Training must be done with scikit-learn. 
+      The python script DSP/Testing/PatternGenerations/Bayes.py is showing how
+      to generate parameters for CMSIS-DSP from the corresponding trained python object.
+      
+      - New folder DistanceFunctions: Distance functions for clustering algorithms
+
+      - New support functions:
+        arm_barycenter_f32 and arm_weighted_sum_f32
+
+      - New statistics functions :
+        arm_entropy_f32, arm_kullback_leibler_f32, arm_logsumexp_f32
+        and arm_logsumexp_dot_prod_f32
+
+      - New testing framework:
+        Developed for our internal needs. We have released it but won't give
+        support for the first few releases since it is a work in progress.
+
+      - Improvements to the cmake build:
+        It is more easy to switch toolchains. CMAKE_PREFIX_PATH can be used.
+
+    </td>
+  </tr>
   <tr>
     <td>V1.7.0</td>
     <td>