/* ---------------------------------------------------------------------- * Project: CMSIS DSP Library * Title: arm_rms_q15.c * Description: Root Mean Square of the elements of a 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" /** * @addtogroup RMS * @{ */ /** * @brief Root Mean Square 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 rms value returned here * @return none. * * @details * Scaling and Overflow Behavior: * * \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_rms_q15( q15_t * pSrc, uint32_t blockSize, q15_t * pResult) { q63_t sum = 0; /* accumulator */ #if defined (ARM_MATH_DSP) /* Run the below code for Cortex-M4 and Cortex-M3 */ q31_t in; /* temporary variable to store the input value */ q15_t in1; /* temporary variable to store the input value */ uint32_t blkCnt; /* loop counter */ /* 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 the squares and then store the results in a temporary variable, sum */ in = *__SIMD32(pSrc)++; sum = __SMLALD(in, in, sum); in = *__SIMD32(pSrc)++; sum = __SMLALD(in, in, sum); /* 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 the squares and then store the results in a temporary variable, sum */ in1 = *pSrc++; sum = __SMLALD(in1, in1, sum); /* Decrement the loop counter */ blkCnt--; } /* Truncating and saturating the accumulator to 1.15 format */ /* Store the result in the destination */ arm_sqrt_q15(__SSAT((sum / (q63_t)blockSize) >> 15, 16), pResult); #else /* Run the below code for Cortex-M0 */ q15_t in; /* temporary variable to store the input value */ uint32_t blkCnt; /* loop counter */ /* 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 the squares and then store the results in a temporary variable, sum */ in = *pSrc++; sum += ((q31_t) in * in); /* Decrement the loop counter */ blkCnt--; } /* Truncating and saturating the accumulator to 1.15 format */ /* Store the result in the destination */ arm_sqrt_q15(__SSAT((sum / (q63_t)blockSize) >> 15, 16), pResult); #endif /* #if defined (ARM_MATH_DSP) */ } /** * @} end of RMS group */