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/* ----------------------------------------------------------------------------
* Copyright (C) 2010-2014 ARM Limited. All rights reserved.
*
* $Date: 19. March 2015
* $Revision: V.1.4.5
*
* Project: CMSIS DSP Library
* Title: arm_correlate_f32.c
*
* Description: Correlation of floating-point 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
*/
/**
* @defgroup Corr Correlation
*
* Correlation is a mathematical operation that is similar to convolution.
* As with convolution, correlation uses two signals to produce a third signal.
* The underlying algorithms in correlation and convolution are identical except that one of the inputs is flipped in convolution.
* Correlation is commonly used to measure the similarity between two signals.
* It has applications in pattern recognition, cryptanalysis, and searching.
* The CMSIS library provides correlation functions for Q7, Q15, Q31 and floating-point data types.
* Fast versions of the Q15 and Q31 functions are also provided.
*
* \par Algorithm
* Let <code>a[n]</code> and <code>b[n]</code> be sequences of length <code>srcALen</code> and <code>srcBLen</code> samples respectively.
* The convolution of the two signals is denoted by
* <pre>
* c[n] = a[n] * b[n]
* </pre>
* In correlation, one of the signals is flipped in time
* <pre>
* c[n] = a[n] * b[-n]
* </pre>
*
* \par
* and this is mathematically defined as
* \image html CorrelateEquation.gif
* \par
* The <code>pSrcA</code> points to the first input vector of length <code>srcALen</code> and <code>pSrcB</code> points to the second input vector of length <code>srcBLen</code>.
* The result <code>c[n]</code> is of length <code>2 * max(srcALen, srcBLen) - 1</code> and is defined over the interval <code>n=0, 1, 2, ..., (2 * max(srcALen, srcBLen) - 2)</code>.
* The output result is written to <code>pDst</code> and the calling function must allocate <code>2 * max(srcALen, srcBLen) - 1</code> words for the result.
*
* <b>Note</b>
* \par
* The <code>pDst</code> should be initialized to all zeros before being used.
*
* <b>Fixed-Point Behavior</b>
* \par
* Correlation requires summing up a large number of intermediate products.
* As such, the Q7, Q15, and Q31 functions run a risk of overflow and saturation.
* Refer to the function specific documentation below for further details of the particular algorithm used.
*
*
* <b>Fast Versions</b>
*
* \par
* Fast versions are supported for Q31 and Q15. Cycles for Fast versions are less compared to Q31 and Q15 of correlate and the design requires
* the input signals should be scaled down to avoid intermediate overflows.
*
*
* <b>Opt Versions</b>
*
* \par
* Opt versions are supported for Q15 and Q7. Design uses internal scratch buffer for getting good optimisation.
* These versions are optimised in cycles and consumes more memory(Scratch memory) compared to Q15 and Q7 versions of correlate
*/
/**
* @addtogroup Corr
* @{
*/
/**
* @brief Correlation of floating-point 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 2 * max(srcALen, srcBLen) - 1.
* @return none.
*/
void arm_correlate_f32(
float32_t * pSrcA,
uint32_t srcALen,
float32_t * pSrcB,
uint32_t srcBLen,
float32_t * pDst)
{
#ifndef ARM_MATH_CM0_FAMILY
/* Run the below code for Cortex-M4 and Cortex-M3 */
float32_t *pIn1; /* inputA pointer */
float32_t *pIn2; /* inputB pointer */
float32_t *pOut = pDst; /* output pointer */
float32_t *px; /* Intermediate inputA pointer */
float32_t *py; /* Intermediate inputB pointer */
float32_t *pSrc1; /* Intermediate pointers */
float32_t sum, acc0, acc1, acc2, acc3; /* Accumulators */
float32_t x0, x1, x2, x3, c0; /* temporary variables for holding input and coefficient values */
uint32_t j, k = 0u, count, blkCnt, outBlockSize, blockSize1, blockSize2, blockSize3; /* loop counters */
int32_t inc = 1; /* Destination address modifier */
/* 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 */
/* But CORR(x, y) is reverse of CORR(y, x) */
/* So, when srcBLen > srcALen, output pointer is made to point to the end of the output buffer */
/* and the destination pointer modifier, inc is set to -1 */
/* If srcALen > srcBLen, zero pad has to be done to srcB to make the two inputs of same length */
/* But to improve the performance,
* we assume zeroes in the output instead of zero padding either of the the inputs*/
/* If srcALen > srcBLen,
* (srcALen - srcBLen) zeroes has to included in the starting of the output buffer */
/* If srcALen < srcBLen,
* (srcALen - srcBLen) zeroes has to included in the ending of the output buffer */
if(srcALen >= srcBLen)
{
/* Initialization of inputA pointer */
pIn1 = pSrcA;
/* Initialization of inputB pointer */
pIn2 = pSrcB;
/* Number of output samples is calculated */
outBlockSize = (2u * srcALen) - 1u;
/* When srcALen > srcBLen, zero padding has to be done to srcB
* to make their lengths equal.
* Instead, (outBlockSize - (srcALen + srcBLen - 1))
* number of output samples are made zero */
j = outBlockSize - (srcALen + (srcBLen - 1u));
/* Updating the pointer position to non zero value */
pOut += j;
//while(j > 0u)
//{
// /* Zero is stored in the destination buffer */
// *pOut++ = 0.0f;
// /* Decrement the loop counter */
// j--;
//}
}
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;
/* CORR(x, y) = Reverse order(CORR(y, x)) */
/* Hence set the destination pointer to point to the last output sample */
pOut = pDst + ((srcALen + srcBLen) - 2u);
/* Destination address modifier is set to -1 */
inc = -1;
}
/* The function is internally
* divided into three parts according to the number of multiplications that has to be
* taken place between inputA samples and inputB samples. In the first part of the
* algorithm, the multiplications increase by one for every iteration.
* In the second part of the algorithm, srcBLen number of multiplications are done.
* In the third part 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);
blockSize3 = blockSize1;
/* --------------------------
* Initializations of stage1
* -------------------------*/
/* sum = x[0] * y[srcBlen - 1]
* sum = x[0] * y[srcBlen-2] + x[1] * y[srcBlen - 1]
* ....
* sum = x[0] * y[0] + x[1] * y[1] +...+ x[srcBLen - 1] * y[srcBLen - 1]
*/
/* 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 */
pSrc1 = pIn2 + (srcBLen - 1u);
py = pSrc1;
/* ------------------------
* Stage1 process
* ----------------------*/
/* The first stage starts here */
while(blockSize1 > 0u)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* 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)
{
/* x[0] * y[srcBLen - 4] */
sum += *px++ * *py++;
/* x[1] * y[srcBLen - 3] */
sum += *px++ * *py++;
/* x[2] * y[srcBLen - 2] */
sum += *px++ * *py++;
/* x[3] * y[srcBLen - 1] */
sum += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* 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-accumulate */
/* x[0] * y[srcBLen - 1] */
sum += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut = sum;
/* Destination pointer is updated according to the address modifier, inc */
pOut += inc;
/* Update the inputA and inputB pointers for next MAC calculation */
py = pSrc1 - count;
px = pIn1;
/* Increment the MAC count */
count++;
/* Decrement the loop counter */
blockSize1--;
}
/* --------------------------
* Initializations of stage2
* ------------------------*/
/* sum = x[0] * y[0] + x[1] * y[1] +...+ x[srcBLen-1] * y[srcBLen-1]
* sum = x[1] * y[0] + x[2] * y[1] +...+ x[srcBLen] * y[srcBLen-1]
* ....
* sum = x[srcALen-srcBLen-2] * y[0] + x[srcALen-srcBLen-1] * y[1] +...+ x[srcALen-1] * y[srcBLen-1]
*/
/* Working pointer of inputA */
px = pIn1;
/* Working pointer of inputB */
py = pIn2;
/* count is 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, to loop unroll the srcBLen loop */
if(srcBLen >= 4u)
{
/* Loop unroll over blockSize2, by 4 */
blkCnt = blockSize2 >> 2u;
while(blkCnt > 0u)
{
/* Set all accumulators to zero */
acc0 = 0.0f;
acc1 = 0.0f;
acc2 = 0.0f;
acc3 = 0.0f;
/* read x[0], x[1], x[2] samples */
x0 = *(px++);
x1 = *(px++);
x2 = *(px++);
/* 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 y[0] sample */
c0 = *(py++);
/* Read x[3] sample */
x3 = *(px++);
/* Perform the multiply-accumulate */
/* acc0 += x[0] * y[0] */
acc0 += x0 * c0;
/* acc1 += x[1] * y[0] */
acc1 += x1 * c0;
/* acc2 += x[2] * y[0] */
acc2 += x2 * c0;
/* acc3 += x[3] * y[0] */
acc3 += x3 * c0;
/* Read y[1] sample */
c0 = *(py++);
/* Read x[4] sample */
x0 = *(px++);
/* Perform the multiply-accumulate */
/* acc0 += x[1] * y[1] */
acc0 += x1 * c0;
/* acc1 += x[2] * y[1] */
acc1 += x2 * c0;
/* acc2 += x[3] * y[1] */
acc2 += x3 * c0;
/* acc3 += x[4] * y[1] */
acc3 += x0 * c0;
/* Read y[2] sample */
c0 = *(py++);
/* Read x[5] sample */
x1 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[2] * y[2] */
acc0 += x2 * c0;
/* acc1 += x[3] * y[2] */
acc1 += x3 * c0;
/* acc2 += x[4] * y[2] */
acc2 += x0 * c0;
/* acc3 += x[5] * y[2] */
acc3 += x1 * c0;
/* Read y[3] sample */
c0 = *(py++);
/* Read x[6] sample */
x2 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[3] * y[3] */
acc0 += x3 * c0;
/* acc1 += x[4] * y[3] */
acc1 += x0 * c0;
/* acc2 += x[5] * y[3] */
acc2 += x1 * c0;
/* acc3 += x[6] * y[3] */
acc3 += x2 * c0;
} while(--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)
{
/* Read y[4] sample */
c0 = *(py++);
/* Read x[7] sample */
x3 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[4] * y[4] */
acc0 += x0 * c0;
/* acc1 += x[5] * y[4] */
acc1 += x1 * c0;
/* acc2 += x[6] * y[4] */
acc2 += x2 * c0;
/* acc3 += x[7] * y[4] */
acc3 += x3 * c0;
/* Reuse the present samples for the next MAC */
x0 = x1;
x1 = x2;
x2 = x3;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut = acc0;
/* Destination pointer is updated according to the address modifier, inc */
pOut += inc;
*pOut = acc1;
pOut += inc;
*pOut = acc2;
pOut += inc;
*pOut = acc3;
pOut += inc;
/* Increment the pointer pIn1 index, count by 4 */
count += 4u;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pIn2;
/* 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 = 0.0f;
/* 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 += *px++ * *py++;
sum += *px++ * *py++;
sum += *px++ * *py++;
sum += *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-accumulate */
sum += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut = sum;
/* Destination pointer is updated according to the address modifier, inc */
pOut += inc;
/* Increment the pointer pIn1 index, count by 1 */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pIn2;
/* 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 = 0.0f;
/* Loop over srcBLen */
k = srcBLen;
while(k > 0u)
{
/* Perform the multiply-accumulate */
sum += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut = sum;
/* Destination pointer is updated according to the address modifier, inc */
pOut += inc;
/* Increment the pointer pIn1 index, count by 1 */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pIn2;
/* Decrement the loop counter */
blkCnt--;
}
}
/* --------------------------
* Initializations of stage3
* -------------------------*/
/* sum += x[srcALen-srcBLen+1] * y[0] + x[srcALen-srcBLen+2] * y[1] +...+ x[srcALen-1] * y[srcBLen-1]
* sum += x[srcALen-srcBLen+2] * y[0] + x[srcALen-srcBLen+3] * y[1] +...+ x[srcALen-1] * y[srcBLen-1]
* ....
* sum += x[srcALen-2] * y[0] + x[srcALen-1] * y[1]
* sum += x[srcALen-1] * y[0]
*/
/* In this stage the MAC operations are decreased by 1 for every iteration.
The count variable holds the number of MAC operations performed */
count = srcBLen - 1u;
/* Working pointer of inputA */
pSrc1 = pIn1 + (srcALen - (srcBLen - 1u));
px = pSrc1;
/* Working pointer of inputB */
py = pIn2;
/* -------------------
* Stage3 process
* ------------------*/
while(blockSize3 > 0u)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* 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 */
/* sum += x[srcALen - srcBLen + 4] * y[3] */
sum += *px++ * *py++;
/* sum += x[srcALen - srcBLen + 3] * y[2] */
sum += *px++ * *py++;
/* sum += x[srcALen - srcBLen + 2] * y[1] */
sum += *px++ * *py++;
/* sum += x[srcALen - srcBLen + 1] * y[0] */
sum += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* 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 += *px++ * *py++;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut = sum;
/* Destination pointer is updated according to the address modifier, inc */
pOut += inc;
/* Update the inputA and inputB pointers for next MAC calculation */
px = ++pSrc1;
py = pIn2;
/* Decrement the MAC count */
count--;
/* Decrement the loop counter */
blockSize3--;
}
#else
/* Run the below code for Cortex-M0 */
float32_t *pIn1 = pSrcA; /* inputA pointer */
float32_t *pIn2 = pSrcB + (srcBLen - 1u); /* inputB pointer */
float32_t sum; /* Accumulator */
uint32_t i = 0u, j; /* loop counters */
uint32_t inv = 0u; /* Reverse order flag */
uint32_t tot = 0u; /* Length */
/* 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 */
/* But CORR(x, y) is reverse of CORR(y, x) */
/* So, when srcBLen > srcALen, output pointer is made to point to the end of the output buffer */
/* and a varaible, inv is set to 1 */
/* If lengths are not equal then zero pad has to be done to make the two
* inputs of same length. But to improve the performance, we assume zeroes
* in the output instead of zero padding either of the the inputs*/
/* If srcALen > srcBLen, (srcALen - srcBLen) zeroes has to included in the
* starting of the output buffer */
/* If srcALen < srcBLen, (srcALen - srcBLen) zeroes has to included in the
* ending of the output buffer */
/* Once the zero padding is done the remaining of the output is calcualted
* using convolution but with the shorter signal time shifted. */
/* Calculate the length of the remaining sequence */
tot = ((srcALen + srcBLen) - 2u);
if(srcALen > srcBLen)
{
/* Calculating the number of zeros to be padded to the output */
j = srcALen - srcBLen;
/* Initialise the pointer after zero padding */
pDst += j;
}
else if(srcALen < srcBLen)
{
/* Initialization to inputB pointer */
pIn1 = pSrcB;
/* Initialization to the end of inputA pointer */
pIn2 = pSrcA + (srcALen - 1u);
/* Initialisation of the pointer after zero padding */
pDst = pDst + tot;
/* Swapping the lengths */
j = srcALen;
srcALen = srcBLen;
srcBLen = j;
/* Setting the reverse flag */
inv = 1;
}
/* Loop to calculate convolution for output length number of times */
for (i = 0u; i <= tot; i++)
{
/* Initialize sum with zero to carry on MAC operations */
sum = 0.0f;
/* Loop to perform MAC operations according to convolution equation */
for (j = 0u; j <= i; j++)
{
/* Check the array limitations */
if((((i - j) < srcBLen) && (j < srcALen)))
{
/* z[i] += x[i-j] * y[j] */
sum += pIn1[j] * pIn2[-((int32_t) i - j)];
}
}
/* Store the output in the destination buffer */
if(inv == 1)
*pDst-- = sum;
else
*pDst++ = sum;
}
#endif /* #ifndef ARM_MATH_CM0_FAMILY */
}
/**
* @} end of Corr group
*/