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CMSIS-DSP: Corrected Doxygen warnings.

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pull/19/head
Christophe Favergeon 6 years ago
parent 08385a3112
commit 7a8a02f976
18 changed files with 98 additions and 66 deletions
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1
Examples/ARM/arm_matrix_example/arm_matrix_example_f32.c
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@ -66,7 +66,6 @@
*
* \par Block Diagram:
* \par
* \image html matrixExample.gif
*
* \par Variables Description:
* \par

61
Include/arm_math.h
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@ -7002,6 +7002,7 @@ typedef struct
/**
* @brief SVM linear instance init function
* @param[in] S Parameters for SVM functions
* @param[in] nbOfSupportVectors Number of support vectors
* @param[in] vectorDimension Dimension of vector space
* @param[in] intercept Intercept
@ -7023,9 +7024,9 @@ 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] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the linear SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/
@ -7037,6 +7038,7 @@ void arm_svm_linear_predict_f32(const arm_svm_linear_instance_f32 *S,
/**
* @brief SVM polynomial instance init function
* @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
* @param[in] intercept Intercept
@ -7065,9 +7067,9 @@ 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] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the polynomial SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/
@ -7079,6 +7081,7 @@ void arm_svm_polynomial_predict_f32(const arm_svm_polynomial_instance_f32 *S,
/**
* @brief SVM radial basis function instance init function
* @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
* @param[in] intercept Intercept
@ -7102,9 +7105,9 @@ 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] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the rbf SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/
@ -7115,6 +7118,7 @@ void arm_svm_rbf_predict_f32(const arm_svm_rbf_instance_f32 *S,
/**
* @brief SVM sigmoid instance init function
* @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
* @param[in] intercept Intercept
@ -7140,9 +7144,9 @@ 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] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the rbf SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/
@ -7168,9 +7172,9 @@ typedef struct
/**
* @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
* @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
*
*/
@ -7198,7 +7202,7 @@ uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_ins
* The max xm of the values if 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] in points to an array of input values.
* @param[in] blockSize number of samples in the input array.
* @return LogSumExp
*
@ -7212,10 +7216,10 @@ float32_t arm_logsumexp_f32(const float32_t *in, uint32_t blockSize);
*
* Vectors are containing the log of the samples
*
* @param[in] *pSrcA points to the first input vector
* @param[in] *pSrcB points to the second input vector
* @param[in] pSrcA points to the first input vector
* @param[in] pSrcB points to the second input vector
* @param[in] blockSize number of samples in each vector
* @param[in] *pTmpBuffer temporary buffer of length blockSize
* @param[in] pTmpBuffer temporary buffer of length blockSize
* @return The log of the dot product .
*
*/
@ -7229,7 +7233,7 @@ 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] pSrcA points to an array of input values.
* @param[in] blockSize number of samples in the input array.
* @return Entropy -Sum(p ln p)
*
@ -7242,8 +7246,8 @@ 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] 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)
*
@ -7257,8 +7261,8 @@ 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] 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
*
@ -7272,9 +7276,9 @@ float32_t arm_weighted_sum_f32(const float32_t *in
* @brief Barycenter
*
*
* @param[in] *in List of points
* @param[in] *in List of weights
* @param[out] *out Barycenter
* @param[in] in List of points
* @param[in] weights Weights of the points
* @param[out] out Barycenter
* @param[in] nbVectors number of vectors
* @param[in] vecDim Dimension of space
* @return None
@ -7411,7 +7415,8 @@ float32_t arm_minkowski_distance_f32(const float32_t *pA,const float32_t *pB, in
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @param[in] order Distance order
* @param[in] blockSize Number of samples
* @return distance
*
*/

1
Source/CommonTables/arm_common_tables.c
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@ -48270,6 +48270,7 @@ const q15_t __ALIGNED(4) realCoefBQ15[8192] = {
*/
#if !defined(ARM_DSP_CONFIG_TABLES) || defined(ARM_ALL_FFT_TABLES) || defined(ARM_TABLE_DCT4_Q15_128)
const q15_t __ALIGNED(4) WeightsQ15_128[256] = {
(q15_t)0x7fff, (q15_t)0x0, (q15_t)0x7ffd, (q15_t)0xfe6e, (q15_t)0x7ff6, (q15_t)0xfcdc, (q15_t)0x7fe9, (q15_t)0xfb4a,
(q15_t)0x7fd8, (q15_t)0xf9b9, (q15_t)0x7fc2, (q15_t)0xf827, (q15_t)0x7fa7, (q15_t)0xf696, (q15_t)0x7f87, (q15_t)0xf505,

14
Source/DistanceFunctions/arm_dice_distance.c
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@ -36,6 +36,13 @@
* @{
*/
extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
, const uint32_t *pB
, uint32_t numberOfBools
, uint32_t *cTT
, uint32_t *cTF
, uint32_t *cFT
);
/**
* @brief Dice distance between two vectors
@ -46,13 +53,6 @@
* @return distance
*
*/
extern void arm_boolean_distance_TT_TF_FT(const uint32_t *pA
, const uint32_t *pB
, uint32_t numberOfBools
, uint32_t *cTT
, uint32_t *cTF
, uint32_t *cFT
);
float32_t arm_dice_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools)
{

40
Source/DistanceFunctions/arm_jensenshannon_distance_f32.c
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@ -37,6 +37,17 @@
*/
static inline double rel_entr(double x, double y)
{
return (x * log(x / y));
}
#if defined(ARM_MATH_NEON)
#include "NEMath.h"
/**
* @brief Jensen-Shannon distance between two vectors
*
@ -57,14 +68,6 @@
*
*/
static inline double rel_entr(double x, double y)
{
return (x * log(x / y));
}
#if defined(ARM_MATH_NEON)
#include "NEMath.h"
float32_t arm_jensenshannon_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize)
{
@ -127,6 +130,27 @@ float32_t arm_jensenshannon_distance_f32(const float32_t *pA,const float32_t *pB
#else
/**
* @brief Jensen-Shannon distance between two vectors
*
* This function is assuming that elements of second vector are > 0
* and 0 only when the corresponding element of first vector is 0.
* Otherwise the result of the computation does not make sense
* and for speed reasons, the cases returning NaN or Infinity are not
* managed.
*
* When the function is computing x log (x / y) with x == 0 and y == 0,
* it will compute the right result (0) but a division by zero will occur
* and should be ignored in client code.
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_jensenshannon_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize)
{
float32_t left, right,sum, result, tmp;

4
Source/DistanceFunctions/arm_minkowski_distance_f32.c
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@ -42,8 +42,8 @@
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] n Norm order (>= 2)
* @param[in] blockSize vector length
* @param[in] order Distance order
* @param[in] blockSize Number of samples
* @return distance
*
*/

1
Source/SVMFunctions/arm_svm_linear_init_f32.c
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@ -47,6 +47,7 @@
/**
* @brief SVM linear instance init function
* @param[in] S Parameters for the SVM function
* @param[in] nbOfSupportVectors Number of support vectors
* @param[in] vectorDimension Dimension of vector space
* @param[in] intercept Intercept

6
Source/SVMFunctions/arm_svm_linear_predict_f32.c
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@ -37,9 +37,9 @@
/**
* @brief SVM linear prediction
* @param[in] *S points to an instance of the linear SVM structure.
* @param[in] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the linear SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/

1
Source/SVMFunctions/arm_svm_polynomial_init_f32.c
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@ -38,6 +38,7 @@
/**
* @brief SVM polynomial instance init function
* @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
* @param[in] intercept Intercept

6
Source/SVMFunctions/arm_svm_polynomial_predict_f32.c
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@ -38,9 +38,9 @@
/**
* @brief SVM polynomial prediction
* @param[in] *S points to an instance of the polynomial SVM structure.
* @param[in] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the polynomial SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/

1
Source/SVMFunctions/arm_svm_rbf_init_f32.c
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@ -37,6 +37,7 @@
/**
* @brief SVM radial basis function instance init function
* @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
* @param[in] intercept Intercept

6
Source/SVMFunctions/arm_svm_rbf_predict_f32.c
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@ -37,9 +37,9 @@
/**
* @brief SVM rbf prediction
* @param[in] *S points to an instance of the rbf SVM structure.
* @param[in] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the rbf SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/

1
Source/SVMFunctions/arm_svm_sigmoid_init_f32.c
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@ -37,6 +37,7 @@
/**
* @brief SVM sigmoid instance init function
* @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
* @param[in] intercept Intercept

6
Source/SVMFunctions/arm_svm_sigmoid_predict_f32.c
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@ -37,9 +37,9 @@
/**
* @brief SVM sigmoid prediction
* @param[in] *S points to an instance of the rbf SVM structure.
* @param[in] vec_in pointer to input vector
* @param[out] *pResult decision value
* @param[in] S points to an instance of the rbf SVM structure.
* @param[in] in pointer to input vector
* @param[out] pResult decision value
* @return none.
*
*/

1
Source/SupportFunctions/arm_barycenter_f32.c
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@ -39,6 +39,7 @@
*
*
* @param[in] *in List of points
* @param[in] *weights Weights of the points
* @param[out] *out Barycenter
* @param[in] nbVectors number of vectors
* @param[in] vecDim Dimension of space

5
Source/TransformFunctions/arm_dct4_init_f32.c
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@ -30,11 +30,10 @@
#include "arm_common_tables.h"
/**
@ingroup DCT4_IDCT4
@ingroup groupTransforms
*/
/**
/**
@addtogroup DCT4_IDCT4
@{
*/

4
Source/TransformFunctions/arm_dct4_init_q15.c
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@ -30,10 +30,10 @@
#include "arm_common_tables.h"
/**
@ingroup DCT4_IDCT4
@ingroup groupTransforms
*/
/**
/**
@addtogroup DCT4_IDCT4
@{
*/

5
Source/TransformFunctions/arm_dct4_init_q31.c
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@ -30,11 +30,10 @@
#include "arm_common_tables.h"
/**
@ingroup DCT4_IDCT4
@ingroup groupTransforms
*/
/**
/**
@addtogroup DCT4_IDCT4
@{
*/

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