text: /* ----------------------------------------------------------------------
  * Copyright (C) 2010-2014 ARM Limited. All rights reserved.
  *
  * $Date:        19. March 2015
  * $Revision:    V.1.4.5
  *
  * Project:      CMSIS DSP Library
  * Title:		arm_conv_q15.c
  *
  * Description:	Convolution of Q15 sequences.
  *
  * 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 groupFilters
   */
  
  /**
   * @addtogroup Conv
   * @{
   */
  
  /**
   * @brief Convolution of Q15 sequences.
   * @param[in] *pSrcA points to the first input sequence.
   * @param[in] srcALen length of the first input sequence.
   * @param[in] *pSrcB points to the second input sequence.
   * @param[in] srcBLen length of the second input sequence.
   * @param[out] *pDst points to the location where the output result is written.  Length srcALen+srcBLen-1.
   * @return none.
   *
   * @details
   * <b>Scaling and Overflow Behavior:</b>
   *
   * \par
   * The function is implemented using a 64-bit internal accumulator.
   * Both inputs are in 1.15 format and multiplications yield a 2.30 result.
   * The 2.30 intermediate results are accumulated in a 64-bit accumulator in 34.30 format.
   * This approach provides 33 guard bits and there is no risk of overflow.
   * The 34.30 result is then truncated to 34.15 format by discarding the low 15 bits and then saturated to 1.15 format.
   *
   * \par
   * Refer to <code>arm_conv_fast_q15()</code> for a faster but less precise version of this function for Cortex-M3 and Cortex-M4.
   *
   * \par
   * Refer the function <code>arm_conv_opt_q15()</code> for a faster implementation of this function using scratch buffers.
   *
   */
  
  void arm_conv_q15(
    q15_t *  pSrcA,
    uint32_t srcALen,
    q15_t *  pSrcB,
    uint32_t srcBLen,
    q15_t *  pDst)
  {
      #if (defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE)
  
      /* Run the below code for Cortex-M4 and Cortex-M3 */
  
      q15_t *pIn1;                                                      /* inputA pointer */
      q15_t *pIn2;                                                      /* inputB pointer */
      q15_t *pOut = pDst;                                               /* output pointer */
      q63_t sum, acc0, acc1, acc2, acc3;                                /* Accumulator */
      q15_t *px;                                                        /* Intermediate inputA pointer  */
      q15_t *py;                                                        /* Intermediate inputB pointer  */
      q15_t *pSrc1, *pSrc2;                                             /* Intermediate pointers */
      q31_t x0, x1, x2, x3, c0;                                         /* Temporary variables to hold state and coefficient values */
      uint32_t blockSize1, blockSize2, blockSize3, j, k, count, blkCnt; /* loop counter */
  
      /* The algorithm implementation is based on the lengths of the inputs. */
      /* srcB is always made to slide across srcA. */
      /* So srcBLen is always considered as shorter or equal to srcALen */
      if (srcALen >= srcBLen)
      {
          /* Initialization of inputA pointer */
          pIn1 = pSrcA;
  
          /* Initialization of inputB pointer */
          pIn2 = pSrcB;
      }
      else
      {
          /* Initialization of inputA pointer */
          pIn1 = pSrcB;
  
          /* Initialization of inputB pointer */
          pIn2 = pSrcA;
  
          /* srcBLen is always considered as shorter or equal to srcALen */
          j       = srcBLen;
          srcBLen = srcALen;
          srcALen = j;
      }
  
      /* conv(x,y) at n = x[n] * y[0] + x[n-1] * y[1] + x[n-2] * y[2] + ...+ x[n-N+1] * y[N -1] */
  
      /* The function is internally
       * divided into three stages according to the number of multiplications that has to be
       * taken place between inputA samples and inputB samples. In the first stage of the
       * algorithm, the multiplications increase by one for every iteration.
       * In the second stage of the algorithm, srcBLen number of multiplications are done.
       * In the third stage of the algorithm, the multiplications decrease by one
       * for every iteration. */
  
      /* The algorithm is implemented in three stages.
       * The loop counters of each stage is initiated here. */
      blockSize1 = srcBLen - 1u;
      blockSize2 = srcALen - (srcBLen - 1u);
  
      /* --------------------------
      * Initializations of stage1
      * -------------------------*/
  
      /* sum = x[0] * y[0]
       * sum = x[0] * y[1] + x[1] * y[0]
       * ....
       * sum = x[0] * y[srcBlen - 1] + x[1] * y[srcBlen - 2] +...+ x[srcBLen - 1] * y[0]
       */
  
      /* In this stage the MAC operations are increased by 1 for every iteration.
       * The count variable holds the number of MAC operations performed */
      count = 1u;
  
      /* Working pointer of inputA */
      px = pIn1;
  
      /* Working pointer of inputB */
      py = pIn2;
  
  
      /* ------------------------
       * Stage1 process
       * ----------------------*/
  
      /* For loop unrolling by 4, this stage is divided into two. */
      /* First part of this stage computes the MAC operations less than 4 */
      /* Second part of this stage computes the MAC operations greater than or equal to 4 */
  
      /* The first part of the stage starts here */
      while ((count < 4u) && (blockSize1 > 0u))
      {
          /* Accumulator is made zero for every iteration */
          sum = 0;
  
          /* Loop over number of MAC operations between
           * inputA samples and inputB samples */
          k = count;
  
          while (k > 0u)
          {
              /* Perform the multiply-accumulates */
              sum = __SMLALD(*px++, *py--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* Store the result in the accumulator in the destination buffer. */
          *pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
  
          /* Update the inputA and inputB pointers for next MAC calculation */
          py = pIn2 + count;
          px = pIn1;
  
          /* Increment the MAC count */
          count++;
  
          /* Decrement the loop counter */
          blockSize1--;
      }
  
      /* The second part of the stage starts here */
      /* The internal loop, over count, is unrolled by 4 */
  
      /* To, read the last two inputB samples using SIMD:
       * y[srcBLen] and y[srcBLen-1] coefficients, py is decremented by 1 */
      py = py - 1;
  
      while (blockSize1 > 0u)
      {
          /* Accumulator is made zero for every iteration */
          sum = 0;
  
          /* Apply loop unrolling and compute 4 MACs simultaneously. */
          k = count >> 2u;
  
          /* First part of the processing with loop unrolling.  Compute 4 MACs at a time.
          ** a second loop below computes MACs for the remaining 1 to 3 samples. */
          while (k > 0u)
          {
              /* Perform the multiply-accumulates */
              /* x[0], x[1] are multiplied with y[srcBLen - 1], y[srcBLen - 2] respectively */
              sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
              /* x[2], x[3] are multiplied with y[srcBLen - 3], y[srcBLen - 4] respectively */
              sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* For the next MAC operations, the pointer py is used without SIMD
           * So, py is incremented by 1 */
          py = py + 1u;
  
          /* If the count is not a multiple of 4, compute any remaining MACs here.
          ** No loop unrolling is used. */
          k = count % 0x4u;
  
          while (k > 0u)
          {
              /* Perform the multiply-accumulates */
              sum = __SMLALD(*px++, *py--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* Store the result in the accumulator in the destination buffer. */
          *pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
  
          /* Update the inputA and inputB pointers for next MAC calculation */
          py = pIn2 + (count - 1u);
          px = pIn1;
  
          /* Increment the MAC count */
          count++;
  
          /* Decrement the loop counter */
          blockSize1--;
      }
  
      /* --------------------------
       * Initializations of stage2
       * ------------------------*/
  
      /* sum = x[0] * y[srcBLen-1] + x[1] * y[srcBLen-2] +...+ x[srcBLen-1] * y[0]
       * sum = x[1] * y[srcBLen-1] + x[2] * y[srcBLen-2] +...+ x[srcBLen] * y[0]
       * ....
       * sum = x[srcALen-srcBLen-2] * y[srcBLen-1] + x[srcALen] * y[srcBLen-2] +...+ x[srcALen-1] * y[0]
       */
  
      /* Working pointer of inputA */
      px = pIn1;
  
      /* Working pointer of inputB */
      pSrc2 = pIn2 + (srcBLen - 1u);
      py    = pSrc2;
  
      /* count is the index by which the pointer pIn1 to be incremented */
      count = 0u;
  
  
      /* --------------------
      * Stage2 process
      * -------------------*/
  
      /* Stage2 depends on srcBLen as in this stage srcBLen number of MACS are performed.
       * So, to loop unroll over blockSize2,
       * srcBLen should be greater than or equal to 4 */
      if (srcBLen >= 4u)
      {
          /* Loop unroll over blockSize2, by 4 */
          blkCnt = blockSize2 >> 2u;
  
          while (blkCnt > 0u)
          {
              py = py - 1u;
  
              /* Set all accumulators to zero */
              acc0 = 0;
              acc1 = 0;
              acc2 = 0;
              acc3 = 0;
  
  
              /* read x[0], x[1] samples */
              x0 = *__SIMD32(px);
              /* read x[1], x[2] samples */
              x1  = _SIMD32_OFFSET(px + 1);
              px += 2u;
  
  
              /* Apply loop unrolling and compute 4 MACs simultaneously. */
              k = srcBLen >> 2u;
  
              /* First part of the processing with loop unrolling.  Compute 4 MACs at a time.
              ** a second loop below computes MACs for the remaining 1 to 3 samples. */
              do
              {
                  /* Read the last two inputB samples using SIMD:
                   * y[srcBLen - 1] and y[srcBLen - 2] */
                  c0 = *__SIMD32(py)--;
  
                  /* acc0 +=  x[0] * y[srcBLen - 1] + x[1] * y[srcBLen - 2] */
                  acc0 = __SMLALDX(x0, c0, acc0);
  
                  /* acc1 +=  x[1] * y[srcBLen - 1] + x[2] * y[srcBLen - 2] */
                  acc1 = __SMLALDX(x1, c0, acc1);
  
                  /* Read x[2], x[3] */
                  x2 = *__SIMD32(px);
  
                  /* Read x[3], x[4] */
                  x3 = _SIMD32_OFFSET(px + 1);
  
                  /* acc2 +=  x[2] * y[srcBLen - 1] + x[3] * y[srcBLen - 2] */
                  acc2 = __SMLALDX(x2, c0, acc2);
  
                  /* acc3 +=  x[3] * y[srcBLen - 1] + x[4] * y[srcBLen - 2] */
                  acc3 = __SMLALDX(x3, c0, acc3);
  
                  /* Read y[srcBLen - 3] and y[srcBLen - 4] */
                  c0 = *__SIMD32(py)--;
  
                  /* acc0 +=  x[2] * y[srcBLen - 3] + x[3] * y[srcBLen - 4] */
                  acc0 = __SMLALDX(x2, c0, acc0);
  
                  /* acc1 +=  x[3] * y[srcBLen - 3] + x[4] * y[srcBLen - 4] */
                  acc1 = __SMLALDX(x3, c0, acc1);
  
                  /* Read x[4], x[5] */
                  x0 = _SIMD32_OFFSET(px + 2);
  
                  /* Read x[5], x[6] */
                  x1  = _SIMD32_OFFSET(px + 3);
                  px += 4u;
  
                  /* acc2 +=  x[4] * y[srcBLen - 3] + x[5] * y[srcBLen - 4] */
                  acc2 = __SMLALDX(x0, c0, acc2);
  
                  /* acc3 +=  x[5] * y[srcBLen - 3] + x[6] * y[srcBLen - 4] */
                  acc3 = __SMLALDX(x1, c0, acc3);
              }
              while (--k);
  
              /* For the next MAC operations, SIMD is not used
               * So, the 16 bit pointer if inputB, py is updated */
  
              /* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
              ** No loop unrolling is used. */
              k = srcBLen % 0x4u;
  
              if (k == 1u)
              {
                  /* Read y[srcBLen - 5] */
                  c0 = *(py + 1);
  
                  # ifdef  ARM_MATH_BIG_ENDIAN
  
                  c0 = c0 << 16u;
  
                  # else
  
                  c0 = c0 & 0x0000FFFF;
  
                  # endif /*      #ifdef  ARM_MATH_BIG_ENDIAN     */
                         /* Read x[7] */
                  x3 = *__SIMD32(px);
                  px++;
  
                  /* Perform the multiply-accumulates */
                  acc0 = __SMLALD(x0, c0, acc0);
                  acc1 = __SMLALD(x1, c0, acc1);
                  acc2 = __SMLALDX(x1, c0, acc2);
                  acc3 = __SMLALDX(x3, c0, acc3);
              }
  
              if (k == 2u)
              {
                  /* Read y[srcBLen - 5], y[srcBLen - 6] */
                  c0 = _SIMD32_OFFSET(py);
  
                  /* Read x[7], x[8] */
                  x3 = *__SIMD32(px);
  
                  /* Read x[9] */
                  x2  = _SIMD32_OFFSET(px + 1);
                  px += 2u;
  
                  /* Perform the multiply-accumulates */
                  acc0 = __SMLALDX(x0, c0, acc0);
                  acc1 = __SMLALDX(x1, c0, acc1);
                  acc2 = __SMLALDX(x3, c0, acc2);
                  acc3 = __SMLALDX(x2, c0, acc3);
              }
  
              if (k == 3u)
              {
                  /* Read y[srcBLen - 5], y[srcBLen - 6] */
                  c0 = _SIMD32_OFFSET(py);
  
                  /* Read x[7], x[8] */
                  x3 = *__SIMD32(px);
  
                  /* Read x[9] */
                  x2 = _SIMD32_OFFSET(px + 1);
  
                  /* Perform the multiply-accumulates */
                  acc0 = __SMLALDX(x0, c0, acc0);
                  acc1 = __SMLALDX(x1, c0, acc1);
                  acc2 = __SMLALDX(x3, c0, acc2);
                  acc3 = __SMLALDX(x2, c0, acc3);
  
                  c0 = *(py - 1);
  
                  # ifdef  ARM_MATH_BIG_ENDIAN
  
                  c0 = c0 << 16u;
                  # else
  
                  c0 = c0 & 0x0000FFFF;
                  # endif /*      #ifdef  ARM_MATH_BIG_ENDIAN     */
                         /* Read x[10] */
                  x3  = _SIMD32_OFFSET(px + 2);
                  px += 3u;
  
                  /* Perform the multiply-accumulates */
                  acc0 = __SMLALDX(x1, c0, acc0);
                  acc1 = __SMLALD(x2, c0, acc1);
                  acc2 = __SMLALDX(x2, c0, acc2);
                  acc3 = __SMLALDX(x3, c0, acc3);
              }
  
  
              /* Store the results in the accumulators in the destination buffer. */
  
              # ifndef  ARM_MATH_BIG_ENDIAN
  
              *__SIMD32(pOut)++ =
                __PKHBT(__SSAT((acc0 >> 15), 16), __SSAT((acc1 >> 15), 16), 16);
              *__SIMD32(pOut)++ =
                __PKHBT(__SSAT((acc2 >> 15), 16), __SSAT((acc3 >> 15), 16), 16);
  
              # else
  
              *__SIMD32(pOut)++ =
                __PKHBT(__SSAT((acc1 >> 15), 16), __SSAT((acc0 >> 15), 16), 16);
              *__SIMD32(pOut)++ =
                __PKHBT(__SSAT((acc3 >> 15), 16), __SSAT((acc2 >> 15), 16), 16);
  
              # endif /*      #ifndef  ARM_MATH_BIG_ENDIAN    */
  
              /* Increment the pointer pIn1 index, count by 4 */
              count += 4u;
  
              /* Update the inputA and inputB pointers for next MAC calculation */
              px = pIn1 + count;
              py = pSrc2;
  
              /* Decrement the loop counter */
              blkCnt--;
          }
  
          /* If the blockSize2 is not a multiple of 4, compute any remaining output samples here.
          ** No loop unrolling is used. */
          blkCnt = blockSize2 % 0x4u;
  
          while (blkCnt > 0u)
          {
              /* Accumulator is made zero for every iteration */
              sum = 0;
  
              /* Apply loop unrolling and compute 4 MACs simultaneously. */
              k = srcBLen >> 2u;
  
              /* First part of the processing with loop unrolling.  Compute 4 MACs at a time.
              ** a second loop below computes MACs for the remaining 1 to 3 samples. */
              while (k > 0u)
              {
                  /* Perform the multiply-accumulates */
                  sum += (q63_t) ((q31_t) *px++ **py--);
                  sum += (q63_t) ((q31_t) *px++ **py--);
                  sum += (q63_t) ((q31_t) *px++ **py--);
                  sum += (q63_t) ((q31_t) *px++ **py--);
  
                  /* Decrement the loop counter */
                  k--;
              }
  
              /* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
              ** No loop unrolling is used. */
              k = srcBLen % 0x4u;
  
              while (k > 0u)
              {
                  /* Perform the multiply-accumulates */
                  sum += (q63_t) ((q31_t) *px++ **py--);
  
                  /* Decrement the loop counter */
                  k--;
              }
  
              /* Store the result in the accumulator in the destination buffer. */
              *pOut++ = (q15_t) (__SSAT(sum >> 15, 16));
  
              /* Increment the pointer pIn1 index, count by 1 */
              count++;
  
              /* Update the inputA and inputB pointers for next MAC calculation */
              px = pIn1 + count;
              py = pSrc2;
  
              /* Decrement the loop counter */
              blkCnt--;
          }
      }
      else
      {
          /* If the srcBLen is not a multiple of 4,
           * the blockSize2 loop cannot be unrolled by 4 */
          blkCnt = blockSize2;
  
          while (blkCnt > 0u)
          {
              /* Accumulator is made zero for every iteration */
              sum = 0;
  
              /* srcBLen number of MACS should be performed */
              k = srcBLen;
  
              while (k > 0u)
              {
                  /* Perform the multiply-accumulate */
                  sum += (q63_t) ((q31_t) *px++ **py--);
  
                  /* Decrement the loop counter */
                  k--;
              }
  
              /* Store the result in the accumulator in the destination buffer. */
              *pOut++ = (q15_t) (__SSAT(sum >> 15, 16));
  
              /* Increment the MAC count */
              count++;
  
              /* Update the inputA and inputB pointers for next MAC calculation */
              px = pIn1 + count;
              py = pSrc2;
  
              /* Decrement the loop counter */
              blkCnt--;
          }
      }
  
  
      /* --------------------------
      * Initializations of stage3
      * -------------------------*/
  
      /* sum += x[srcALen-srcBLen+1] * y[srcBLen-1] + x[srcALen-srcBLen+2] * y[srcBLen-2] +...+ x[srcALen-1] * y[1]
       * sum += x[srcALen-srcBLen+2] * y[srcBLen-1] + x[srcALen-srcBLen+3] * y[srcBLen-2] +...+ x[srcALen-1] * y[2]
       * ....
       * sum +=  x[srcALen-2] * y[srcBLen-1] + x[srcALen-1] * y[srcBLen-2]
       * sum +=  x[srcALen-1] * y[srcBLen-1]
       */
  
      /* In this stage the MAC operations are decreased by 1 for every iteration.
       * The blockSize3 variable holds the number of MAC operations performed */
  
      blockSize3 = srcBLen - 1u;
  
      /* Working pointer of inputA */
      pSrc1 = (pIn1 + srcALen) - (srcBLen - 1u);
      px    = pSrc1;
  
      /* Working pointer of inputB */
      pSrc2 = pIn2 + (srcBLen - 1u);
      pIn2  = pSrc2 - 1u;
      py    = pIn2;
  
      /* -------------------
      * Stage3 process
      * ------------------*/
  
      /* For loop unrolling by 4, this stage is divided into two. */
      /* First part of this stage computes the MAC operations greater than 4 */
      /* Second part of this stage computes the MAC operations less than or equal to 4 */
  
      /* The first part of the stage starts here */
      j = blockSize3 >> 2u;
  
      while ((j > 0u) && (blockSize3 > 0u))
      {
          /* Accumulator is made zero for every iteration */
          sum = 0;
  
          /* Apply loop unrolling and compute 4 MACs simultaneously. */
          k = blockSize3 >> 2u;
  
          /* First part of the processing with loop unrolling.  Compute 4 MACs at a time.
          ** a second loop below computes MACs for the remaining 1 to 3 samples. */
          while (k > 0u)
          {
              /* x[srcALen - srcBLen + 1], x[srcALen - srcBLen + 2] are multiplied
               * with y[srcBLen - 1], y[srcBLen - 2] respectively */
              sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
  
              /* x[srcALen - srcBLen + 3], x[srcALen - srcBLen + 4] are multiplied
               * with y[srcBLen - 3], y[srcBLen - 4] respectively */
              sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* For the next MAC operations, the pointer py is used without SIMD
           * So, py is incremented by 1 */
          py = py + 1u;
  
          /* If the blockSize3 is not a multiple of 4, compute any remaining MACs here.
          ** No loop unrolling is used. */
          k = blockSize3 % 0x4u;
  
          while (k > 0u)
          {
              /* sum += x[srcALen - srcBLen + 5] * y[srcBLen - 5] */
              sum = __SMLALD(*px++, *py--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* Store the result in the accumulator in the destination buffer. */
          *pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
  
          /* Update the inputA and inputB pointers for next MAC calculation */
          px = ++pSrc1;
          py = pIn2;
  
          /* Decrement the loop counter */
          blockSize3--;
  
          j--;
      }
  
      /* The second part of the stage starts here */
  
      /* SIMD is not used for the next MAC operations,
       * so pointer py is updated to read only one sample at a time */
      py = py + 1u;
  
      while (blockSize3 > 0u)
      {
          /* Accumulator is made zero for every iteration */
          sum = 0;
  
          /* Apply loop unrolling and compute 4 MACs simultaneously. */
          k = blockSize3;
  
          while (k > 0u)
          {
              /* Perform the multiply-accumulates */
              /* sum +=  x[srcALen-1] * y[srcBLen-1] */
              sum = __SMLALD(*px++, *py--, sum);
  
              /* Decrement the loop counter */
              k--;
          }
  
          /* Store the result in the accumulator in the destination buffer. */
          *pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
  
          /* Update the inputA and inputB pointers for next MAC calculation */
          px = ++pSrc1;
          py = pSrc2;
  
          /* Decrement the loop counter */
          blockSize3--;
      }
  
      #else /* if (defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE) */
  
      /* Run the below code for Cortex-M0 */
  
      q15_t *pIn1 = pSrcA; /* input pointer */
      q15_t *pIn2 = pSrcB; /* coefficient pointer */
      q63_t sum;           /* Accumulator */
      uint32_t i, j;       /* loop counter */
  
      /* Loop to calculate output of convolution for output length number of times */
      for (i = 0; i < (srcALen + srcBLen - 1); i++)
      {
          /* Initialize sum with zero to carry on MAC operations */
          sum = 0;
  
          /* Loop to perform MAC operations according to convolution equation */
          for (j = 0; j <= i; j++)
          {
              /* Check the array limitations */
              if (((i - j) < srcBLen) && (j < srcALen))
              {
                  /* z[i] += x[i-j] * y[j] */
                  sum += (q31_t) pIn1[j] * (pIn2[i - j]);
              }
          }
  
          /* Store the output in the destination buffer */
          pDst[i] = (q15_t) __SSAT((sum >> 15u), 16u);
      }
  
      #endif /*  #if (defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE)*/
  } /* arm_conv_q15 */
  
  /**
   * @} end of Conv group
   */
  