/* ---------------------------------------------------------------------- * Copyright (C) 2010-2014 ARM Limited. All rights reserved. * * $Date: 19. March 2015 * $Revision: V.1.4.5 * * 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 * 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_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 */