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153 lines
5.5 KiB
153 lines
5.5 KiB
/* ----------------------------------------------------------------------
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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_rms_q15.c
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*
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* Description: Root Mean Square of the elements of a Q15 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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* @addtogroup RMS
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* @{
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*/
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/**
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* @brief Root Mean Square of the elements of a Q15 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 rms value returned here
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* @return none.
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*
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* @details
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* <b>Scaling and Overflow Behavior:</b>
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*
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* \par
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* The function is implemented using a 64-bit internal accumulator.
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* The input is represented in 1.15 format.
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* Intermediate multiplication yields a 2.30 format, and this
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* result is added without saturation to a 64-bit accumulator in 34.30 format.
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* With 33 guard bits in the accumulator, there is no risk of overflow, and the
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* full precision of the intermediate multiplication is preserved.
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* Finally, the 34.30 result is truncated to 34.15 format by discarding the lower
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* 15 bits, and then saturated to yield a result in 1.15 format.
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*
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*/
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void arm_rms_q15(
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q15_t * pSrc,
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uint32_t blockSize,
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q15_t * pResult)
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{
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q63_t sum = 0; /* accumulator */
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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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q31_t in; /* temporary variable to store the input value */
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q15_t in1; /* temporary variable to store the input value */
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uint32_t blkCnt; /* loop counter */
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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 the squares and then store the results in a temporary variable, sum */
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in = *__SIMD32(pSrc)++;
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sum = __SMLALD(in, in, sum);
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in = *__SIMD32(pSrc)++;
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sum = __SMLALD(in, in, sum);
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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 the squares and then store the results in a temporary variable, sum */
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in1 = *pSrc++;
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sum = __SMLALD(in1, in1, sum);
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Truncating and saturating the accumulator to 1.15 format */
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/* Store the result in the destination */
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arm_sqrt_q15(__SSAT((sum / (q63_t)blockSize) >> 15, 16), pResult);
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#else
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/* Run the below code for Cortex-M0 */
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q15_t in; /* temporary variable to store the input value */
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uint32_t blkCnt; /* loop counter */
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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 the squares and then store the results in a temporary variable, sum */
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in = *pSrc++;
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sum += ((q31_t) in * in);
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Truncating and saturating the accumulator to 1.15 format */
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/* Store the result in the destination */
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arm_sqrt_q15(__SSAT((sum / (q63_t)blockSize) >> 15, 16), 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 RMS group
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*/
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