/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_std_q15.c
* Description: Standard deviation of an array of Q15 vector
*
* $Date: 27. January 2017
* $Revision: V.1.5.1
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "arm_math.h"
/**
* @ingroup groupStats
*/
/**
* @addtogroup STD
* @{
*/
/**
* @brief Standard deviation 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 standard deviation 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_std_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 */
#if defined (ARM_MATH_DSP)
q31_t in; /* input value */
q15_t in1; /* input value */
#else
q15_t in; /* input value */
#endif
if (blockSize == 1U)
{
*pResult = 0;
return;
}
#if defined (ARM_MATH_DSP)
/* Run the below code for Cortex-M4 and Cortex-M3 */
/*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 << 16U) >> 16U);
sum += (in >> 16U);
sumOfSquares = __SMLALD(in, in, sumOfSquares);
in = *__SIMD32(pSrc)++;
sum += ((in << 16U) >> 16U);
sum += (in >> 16U);
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 - 1U));
/* Compute square of mean */
squareOfMean = (q31_t)((q63_t)sum * sum / (q63_t)(blockSize * (blockSize - 1U)));
/* mean of the squares minus the square of the mean. */
/* Compute standard deviation and store the result to the destination */
arm_sqrt_q15(__SSAT((meanOfSquares - squareOfMean) >> 15U, 16U), pResult);
#else
/* Run the below code for Cortex-M0 */
/* 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 - 1U));
/* Compute square of mean */
squareOfMean = (q31_t)((q63_t)sum * sum / (q63_t)(blockSize * (blockSize - 1U)));
/* mean of the squares minus the square of the mean. */
/* Compute standard deviation and store the result to the destination */
arm_sqrt_q15(__SSAT((meanOfSquares - squareOfMean) >> 15U, 16U), pResult);
#endif /* #if defined (ARM_MATH_DSP) */
}
/**
* @} end of STD group
*/