ams-master-23/Drivers/CMSIS/DSP/Source/StatisticsFunctions/arm_rms_f32.c

128 lines
3.6 KiB
C

/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_rms_f32.c
* Description: Root mean square value of an array of F32 type
*
* $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
*/
/**
* @defgroup RMS Root mean square (RMS)
*
*
* Calculates the Root Mean Sqaure of the elements in the input vector.
* The underlying algorithm is used:
*
* <pre>
* Result = sqrt(((pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] * pSrc[blockSize-1]) / blockSize));
* </pre>
*
* There are separate functions for floating point, Q31, and Q15 data types.
*/
/**
* @addtogroup RMS
* @{
*/
/**
* @brief Root Mean Square of the elements of a floating-point vector.
* @param[in] *pSrc points to the input vector
* @param[in] blockSize length of the input vector
* @param[out] *pResult rms value returned here
* @return none.
*
*/
void arm_rms_f32(
float32_t * pSrc,
uint32_t blockSize,
float32_t * pResult)
{
float32_t sum = 0.0f; /* Accumulator */
float32_t in; /* Tempoprary variable to store input value */
uint32_t blkCnt; /* loop counter */
#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[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
/* Compute sum of the squares and then store the result in a temporary variable, sum */
in = *pSrc++;
sum += in * in;
in = *pSrc++;
sum += in * in;
in = *pSrc++;
sum += in * in;
in = *pSrc++;
sum += in * in;
/* 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;
#else
/* Run the below code for Cortex-M0 */
/* Loop over blockSize number of values */
blkCnt = blockSize;
#endif /* #if defined (ARM_MATH_DSP) */
while (blkCnt > 0U)
{
/* C = A[0] * A[0] + A[1] * A[1] + A[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
/* Compute sum of the squares and then store the results in a temporary variable, sum */
in = *pSrc++;
sum += in * in;
/* Decrement the loop counter */
blkCnt--;
}
/* Compute Rms and store the result in the destination */
arm_sqrt_f32(sum / (float32_t) blockSize, pResult);
}
/**
* @} end of RMS group
*/