209 lines
6.5 KiB
C
209 lines
6.5 KiB
C
/* ----------------------------------------------------------------------
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* Copyright (C) 2010-2014 ARM Limited. All rights reserved.
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*
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* $Date: 19. March 2015
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* $Revision: V.1.4.5
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*
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* Project: CMSIS DSP Library
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* Title: arm_std_f32.c
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*
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* Description: Standard deviation of the elements of a floating-point vector.
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*
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* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* - Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* - Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* - Neither the name of ARM LIMITED nor the names of its contributors
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* may be used to endorse or promote products derived from this
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* software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* ---------------------------------------------------------------------------- */
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#include "arm_math.h"
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/**
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* @ingroup groupStats
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*/
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/**
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* @defgroup STD Standard deviation
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*
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* Calculates the standard deviation of the elements in the input vector.
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* The underlying algorithm is used:
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*
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* <pre>
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* Result = sqrt((sumOfSquares - sum<sup>2</sup> / blockSize) / (blockSize - 1))
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*
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* where, sumOfSquares = pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] * pSrc[blockSize-1]
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*
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* sum = pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1]
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* </pre>
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*
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* There are separate functions for floating point, Q31, and Q15 data types.
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*/
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/**
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* @addtogroup STD
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* @{
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*/
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/**
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* @brief Standard deviation of the elements of a floating-point vector.
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* @param[in] *pSrc points to the input vector
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* @param[in] blockSize length of the input vector
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* @param[out] *pResult standard deviation value returned here
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* @return none.
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*
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*/
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void arm_std_f32(
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float32_t * pSrc,
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uint32_t blockSize,
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float32_t * pResult)
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{
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float32_t sum = 0.0f; /* Temporary result storage */
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float32_t sumOfSquares = 0.0f; /* Sum of squares */
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float32_t in; /* input value */
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uint32_t blkCnt; /* loop counter */
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#ifndef ARM_MATH_CM0_FAMILY
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/* Run the below code for Cortex-M4 and Cortex-M3 */
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float32_t meanOfSquares, mean, squareOfMean;
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if(blockSize == 1)
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{
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*pResult = 0;
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return;
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}
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/*loop Unrolling */
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blkCnt = blockSize >> 2u;
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/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
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** a second loop below computes the remaining 1 to 3 samples. */
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while(blkCnt > 0u)
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{
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/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
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/* Compute Sum of squares of the input samples
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* and then store the result in a temporary variable, sum. */
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in = *pSrc++;
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sum += in;
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sumOfSquares += in * in;
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in = *pSrc++;
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sum += in;
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sumOfSquares += in * in;
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in = *pSrc++;
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sum += in;
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sumOfSquares += in * in;
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in = *pSrc++;
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sum += in;
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sumOfSquares += in * in;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
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** No loop unrolling is used. */
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blkCnt = blockSize % 0x4u;
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while(blkCnt > 0u)
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{
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/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
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/* Compute Sum of squares of the input samples
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* and then store the result in a temporary variable, sum. */
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in = *pSrc++;
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sum += in;
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sumOfSquares += in * in;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Compute Mean of squares of the input samples
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* and then store the result in a temporary variable, meanOfSquares. */
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meanOfSquares = sumOfSquares / ((float32_t) blockSize - 1.0f);
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/* Compute mean of all input values */
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mean = sum / (float32_t) blockSize;
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/* Compute square of mean */
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squareOfMean = (mean * mean) * (((float32_t) blockSize) /
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((float32_t) blockSize - 1.0f));
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/* Compute standard deviation and then store the result to the destination */
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arm_sqrt_f32((meanOfSquares - squareOfMean), pResult);
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#else
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/* Run the below code for Cortex-M0 */
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float32_t squareOfSum; /* Square of Sum */
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float32_t var; /* Temporary varaince storage */
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if(blockSize == 1)
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{
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*pResult = 0;
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return;
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}
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/* Loop over blockSize number of values */
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blkCnt = blockSize;
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while(blkCnt > 0u)
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{
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/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
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/* Compute Sum of squares of the input samples
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* and then store the result in a temporary variable, sumOfSquares. */
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in = *pSrc++;
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sumOfSquares += in * in;
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/* C = (A[0] + A[1] + ... + A[blockSize-1]) */
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/* Compute Sum of the input samples
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* and then store the result in a temporary variable, sum. */
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sum += in;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Compute the square of sum */
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squareOfSum = ((sum * sum) / (float32_t) blockSize);
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/* Compute the variance */
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var = ((sumOfSquares - squareOfSum) / (float32_t) (blockSize - 1.0f));
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/* Compute standard deviation and then store the result to the destination */
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arm_sqrt_f32(var, pResult);
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#endif /* #ifndef ARM_MATH_CM0_FAMILY */
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}
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/**
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* @} end of STD group
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*/
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