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/* ----------------------------------------------------------------------
* Copyright (C) 2010-2014 ARM Limited. All rights reserved.
*
* $Date: 12. March 2014
* $Revision: V1.4.4
*
* Project: CMSIS DSP Library
* Title: arm_var_q15.c
*
* Description: Variance of an array of Q15 type.
*
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* - Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* - Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
* - Neither the name of ARM LIMITED nor the names of its contributors
* may be used to endorse or promote products derived from this
* software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
* -------------------------------------------------------------------- */
#include "arm_math.h"
/**
* @ingroup groupStats
*/
/**
* @addtogroup variance
* @{
*/
/**
* @brief Variance of the elements of a Q15 vector.
* @param[in] *pSrc points to the input vector
* @param[in] blockSize length of the input vector
* @param[out] *pResult variance value returned here
* @return none.
*
* @details
* <b>Scaling and Overflow Behavior:</b>
*
* \par
* The function is implemented using a 64-bit internal accumulator.
* The input is represented in 1.15 format.
* Intermediate multiplication yields a 2.30 format, and this
* result is added without saturation to a 64-bit accumulator in 34.30 format.
* With 33 guard bits in the accumulator, there is no risk of overflow, and the
* full precision of the intermediate multiplication is preserved.
* Finally, the 34.30 result is truncated to 34.15 format by discarding the lower
* 15 bits, and then saturated to yield a result in 1.15 format.
*
*/
void arm_var_q15(
q15_t * pSrc,
uint32_t blockSize,
q15_t * pResult)
{
q31_t sum = 0; /* Accumulator */
q31_t meanOfSquares, squareOfMean; /* square of mean and mean of square */
uint32_t blkCnt; /* loop counter */
q63_t sumOfSquares = 0; /* Accumulator */
#ifndef ARM_MATH_CM0_FAMILY
/* Run the below code for Cortex-M4 and Cortex-M3 */
q31_t in; /* input value */
q15_t in1; /* input value */
if(blockSize == 1)
{
*pResult = 0;
return;
}
/*loop Unrolling */
blkCnt = blockSize >> 2u;
/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
** a second loop below computes the remaining 1 to 3 samples. */
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sum. */
in = *__SIMD32(pSrc)++;
sum += ((in << 16) >> 16);
sum += (in >> 16);
sumOfSquares = __SMLALD(in, in, sumOfSquares);
in = *__SIMD32(pSrc)++;
sum += ((in << 16) >> 16);
sum += (in >> 16);
sumOfSquares = __SMLALD(in, in, sumOfSquares);
/* Decrement the loop counter */
blkCnt--;
}
/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
** No loop unrolling is used. */
blkCnt = blockSize % 0x4u;
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sum. */
in1 = *pSrc++;
sumOfSquares = __SMLALD(in1, in1, sumOfSquares);
sum += in1;
/* Decrement the loop counter */
blkCnt--;
}
/* Compute Mean of squares of the input samples
* and then store the result in a temporary variable, meanOfSquares. */
meanOfSquares = (q31_t) (sumOfSquares / (q63_t)(blockSize - 1));
/* Compute square of mean */
squareOfMean = (q31_t)((q63_t)sum * sum / (q63_t)(blockSize * (blockSize - 1)));
/* mean of the squares minus the square of the mean. */
*pResult = (meanOfSquares - squareOfMean) >> 15;
#else
/* Run the below code for Cortex-M0 */
q15_t in; /* input value */
if(blockSize == 1)
{
*pResult = 0;
return;
}
/* Loop over blockSize number of values */
blkCnt = blockSize;
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sumOfSquares. */
in = *pSrc++;
sumOfSquares += (in * in);
/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
/* Compute sum of all input values and then store the result in a temporary variable, sum. */
sum += in;
/* Decrement the loop counter */
blkCnt--;
}
/* Compute Mean of squares of the input samples
* and then store the result in a temporary variable, meanOfSquares. */
meanOfSquares = (q31_t) (sumOfSquares / (q63_t)(blockSize - 1));
/* Compute square of mean */
squareOfMean = (q31_t)((q63_t)sum * sum / (q63_t)(blockSize * (blockSize - 1)));
/* mean of the squares minus the square of the mean. */
*pResult = (meanOfSquares - squareOfMean) >> 15;
#endif /* #ifndef ARM_MATH_CM0_FAMILY */
}
/**
* @} end of variance group
*/
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