+++ /dev/null
-/* ----------------------------------------------------------------------
-* Copyright (C) 2010-2013 ARM Limited. All rights reserved.
-*
-* $Date: 17. January 2013
-* $Revision: V1.4.1
-*
-* Project: CMSIS DSP Library
-* Title: arm_lms_f32.c
-*
-* Description: Processing function for the floating-point LMS filter.
-*
-* 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 LMS Least Mean Square (LMS) Filters
- *
- * LMS filters are a class of adaptive filters that are able to "learn" an unknown transfer functions.
- * LMS filters use a gradient descent method in which the filter coefficients are updated based on the instantaneous error signal.
- * Adaptive filters are often used in communication systems, equalizers, and noise removal.
- * The CMSIS DSP Library contains LMS filter functions that operate on Q15, Q31, and floating-point data types.
- * The library also contains normalized LMS filters in which the filter coefficient adaptation is indepedent of the level of the input signal.
- *
- * An LMS filter consists of two components as shown below.
- * The first component is a standard transversal or FIR filter.
- * The second component is a coefficient update mechanism.
- * The LMS filter has two input signals.
- * The "input" feeds the FIR filter while the "reference input" corresponds to the desired output of the FIR filter.
- * That is, the FIR filter coefficients are updated so that the output of the FIR filter matches the reference input.
- * The filter coefficient update mechanism is based on the difference between the FIR filter output and the reference input.
- * This "error signal" tends towards zero as the filter adapts.
- * The LMS processing functions accept the input and reference input signals and generate the filter output and error signal.
- * \image html LMS.gif "Internal structure of the Least Mean Square filter"
- *
- * The functions operate on blocks of data and each call to the function processes
- * <code>blockSize</code> samples through the filter.
- * <code>pSrc</code> points to input signal, <code>pRef</code> points to reference signal,
- * <code>pOut</code> points to output signal and <code>pErr</code> points to error signal.
- * All arrays contain <code>blockSize</code> values.
- *
- * The functions operate on a block-by-block basis.
- * Internally, the filter coefficients <code>b[n]</code> are updated on a sample-by-sample basis.
- * The convergence of the LMS filter is slower compared to the normalized LMS algorithm.
- *
- * \par Algorithm:
- * The output signal <code>y[n]</code> is computed by a standard FIR filter:
- * <pre>
- * y[n] = b[0] * x[n] + b[1] * x[n-1] + b[2] * x[n-2] + ...+ b[numTaps-1] * x[n-numTaps+1]
- * </pre>
- *
- * \par
- * The error signal equals the difference between the reference signal <code>d[n]</code> and the filter output:
- * <pre>
- * e[n] = d[n] - y[n].
- * </pre>
- *
- * \par
- * After each sample of the error signal is computed, the filter coefficients <code>b[k]</code> are updated on a sample-by-sample basis:
- * <pre>
- * b[k] = b[k] + e[n] * mu * x[n-k], for k=0, 1, ..., numTaps-1
- * </pre>
- * where <code>mu</code> is the step size and controls the rate of coefficient convergence.
- *\par
- * In the APIs, <code>pCoeffs</code> points to a coefficient array of size <code>numTaps</code>.
- * Coefficients are stored in time reversed order.
- * \par
- * <pre>
- * {b[numTaps-1], b[numTaps-2], b[N-2], ..., b[1], b[0]}
- * </pre>
- * \par
- * <code>pState</code> points to a state array of size <code>numTaps + blockSize - 1</code>.
- * Samples in the state buffer are stored in the order:
- * \par
- * <pre>
- * {x[n-numTaps+1], x[n-numTaps], x[n-numTaps-1], x[n-numTaps-2]....x[0], x[1], ..., x[blockSize-1]}
- * </pre>
- * \par
- * Note that the length of the state buffer exceeds the length of the coefficient array by <code>blockSize-1</code> samples.
- * The increased state buffer length allows circular addressing, which is traditionally used in FIR filters,
- * to be avoided and yields a significant speed improvement.
- * The state variables are updated after each block of data is processed.
- * \par Instance Structure
- * The coefficients and state variables for a filter are stored together in an instance data structure.
- * A separate instance structure must be defined for each filter and
- * coefficient and state arrays cannot be shared among instances.
- * There are separate instance structure declarations for each of the 3 supported data types.
- *
- * \par Initialization Functions
- * There is also an associated initialization function for each data type.
- * The initialization function performs the following operations:
- * - Sets the values of the internal structure fields.
- * - Zeros out the values in the state buffer.
- * To do this manually without calling the init function, assign the follow subfields of the instance structure:
- * numTaps, pCoeffs, mu, postShift (not for f32), pState. Also set all of the values in pState to zero.
- *
- * \par
- * Use of the initialization function is optional.
- * However, if the initialization function is used, then the instance structure cannot be placed into a const data section.
- * To place an instance structure into a const data section, the instance structure must be manually initialized.
- * Set the values in the state buffer to zeros before static initialization.
- * The code below statically initializes each of the 3 different data type filter instance structures
- * <pre>
- * arm_lms_instance_f32 S = {numTaps, pState, pCoeffs, mu};
- * arm_lms_instance_q31 S = {numTaps, pState, pCoeffs, mu, postShift};
- * arm_lms_instance_q15 S = {numTaps, pState, pCoeffs, mu, postShift};
- * </pre>
- * where <code>numTaps</code> is the number of filter coefficients in the filter; <code>pState</code> is the address of the state buffer;
- * <code>pCoeffs</code> is the address of the coefficient buffer; <code>mu</code> is the step size parameter; and <code>postShift</code> is the shift applied to coefficients.
- *
- * \par Fixed-Point Behavior:
- * Care must be taken when using the Q15 and Q31 versions of the LMS filter.
- * The following issues must be considered:
- * - Scaling of coefficients
- * - Overflow and saturation
- *
- * \par Scaling of Coefficients:
- * Filter coefficients are represented as fractional values and
- * coefficients are restricted to lie in the range <code>[-1 +1)</code>.
- * The fixed-point functions have an additional scaling parameter <code>postShift</code>.
- * At the output of the filter's accumulator is a shift register which shifts the result by <code>postShift</code> bits.
- * This essentially scales the filter coefficients by <code>2^postShift</code> and
- * allows the filter coefficients to exceed the range <code>[+1 -1)</code>.
- * The value of <code>postShift</code> is set by the user based on the expected gain through the system being modeled.
- *
- * \par Overflow and Saturation:
- * Overflow and saturation behavior of the fixed-point Q15 and Q31 versions are
- * described separately as part of the function specific documentation below.
- */
-
-/**
- * @addtogroup LMS
- * @{
- */
-
-/**
- * @details
- * This function operates on floating-point data types.
- *
- * @brief Processing function for floating-point LMS filter.
- * @param[in] *S points to an instance of the floating-point LMS filter structure.
- * @param[in] *pSrc points to the block of input data.
- * @param[in] *pRef points to the block of reference data.
- * @param[out] *pOut points to the block of output data.
- * @param[out] *pErr points to the block of error data.
- * @param[in] blockSize number of samples to process.
- * @return none.
- */
-
-void arm_lms_f32(
- const arm_lms_instance_f32 * S,
- float32_t * pSrc,
- float32_t * pRef,
- float32_t * pOut,
- float32_t * pErr,
- uint32_t blockSize)
-{
- float32_t *pState = S->pState; /* State pointer */
- float32_t *pCoeffs = S->pCoeffs; /* Coefficient pointer */
- float32_t *pStateCurnt; /* Points to the current sample of the state */
- float32_t *px, *pb; /* Temporary pointers for state and coefficient buffers */
- float32_t mu = S->mu; /* Adaptive factor */
- uint32_t numTaps = S->numTaps; /* Number of filter coefficients in the filter */
- uint32_t tapCnt, blkCnt; /* Loop counters */
- float32_t sum, e, d; /* accumulator, error, reference data sample */
- float32_t w = 0.0f; /* weight factor */
-
- e = 0.0f;
- d = 0.0f;
-
- /* S->pState points to state array which contains previous frame (numTaps - 1) samples */
- /* pStateCurnt points to the location where the new input data should be written */
- pStateCurnt = &(S->pState[(numTaps - 1u)]);
-
- blkCnt = blockSize;
-
-
-#ifndef ARM_MATH_CM0_FAMILY
-
- /* Run the below code for Cortex-M4 and Cortex-M3 */
-
- while(blkCnt > 0u)
- {
- /* Copy the new input sample into the state buffer */
- *pStateCurnt++ = *pSrc++;
-
- /* Initialize pState pointer */
- px = pState;
-
- /* Initialize coeff pointer */
- pb = (pCoeffs);
-
- /* Set the accumulator to zero */
- sum = 0.0f;
-
- /* Loop unrolling. Process 4 taps at a time. */
- tapCnt = numTaps >> 2;
-
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- sum += (*px++) * (*pb++);
- sum += (*px++) * (*pb++);
- sum += (*px++) * (*pb++);
- sum += (*px++) * (*pb++);
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* If the filter length is not a multiple of 4, compute the remaining filter taps */
- tapCnt = numTaps % 0x4u;
-
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- sum += (*px++) * (*pb++);
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* The result in the accumulator, store in the destination buffer. */
- *pOut++ = sum;
-
- /* Compute and store error */
- d = (float32_t) (*pRef++);
- e = d - sum;
- *pErr++ = e;
-
- /* Calculation of Weighting factor for the updating filter coefficients */
- w = e * mu;
-
- /* Initialize pState pointer */
- px = pState;
-
- /* Initialize coeff pointer */
- pb = (pCoeffs);
-
- /* Loop unrolling. Process 4 taps at a time. */
- tapCnt = numTaps >> 2;
-
- /* Update filter coefficients */
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- *pb = *pb + (w * (*px++));
- pb++;
-
- *pb = *pb + (w * (*px++));
- pb++;
-
- *pb = *pb + (w * (*px++));
- pb++;
-
- *pb = *pb + (w * (*px++));
- pb++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* If the filter length is not a multiple of 4, compute the remaining filter taps */
- tapCnt = numTaps % 0x4u;
-
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- *pb = *pb + (w * (*px++));
- pb++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* Advance state pointer by 1 for the next sample */
- pState = pState + 1;
-
- /* Decrement the loop counter */
- blkCnt--;
- }
-
-
- /* Processing is complete. Now copy the last numTaps - 1 samples to the
- satrt of the state buffer. This prepares the state buffer for the
- next function call. */
-
- /* Points to the start of the pState buffer */
- pStateCurnt = S->pState;
-
- /* Loop unrolling for (numTaps - 1u) samples copy */
- tapCnt = (numTaps - 1u) >> 2u;
-
- /* copy data */
- while(tapCnt > 0u)
- {
- *pStateCurnt++ = *pState++;
- *pStateCurnt++ = *pState++;
- *pStateCurnt++ = *pState++;
- *pStateCurnt++ = *pState++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* Calculate remaining number of copies */
- tapCnt = (numTaps - 1u) % 0x4u;
-
- /* Copy the remaining q31_t data */
- while(tapCnt > 0u)
- {
- *pStateCurnt++ = *pState++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
-#else
-
- /* Run the below code for Cortex-M0 */
-
- while(blkCnt > 0u)
- {
- /* Copy the new input sample into the state buffer */
- *pStateCurnt++ = *pSrc++;
-
- /* Initialize pState pointer */
- px = pState;
-
- /* Initialize pCoeffs pointer */
- pb = pCoeffs;
-
- /* Set the accumulator to zero */
- sum = 0.0f;
-
- /* Loop over numTaps number of values */
- tapCnt = numTaps;
-
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- sum += (*px++) * (*pb++);
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* The result is stored in the destination buffer. */
- *pOut++ = sum;
-
- /* Compute and store error */
- d = (float32_t) (*pRef++);
- e = d - sum;
- *pErr++ = e;
-
- /* Weighting factor for the LMS version */
- w = e * mu;
-
- /* Initialize pState pointer */
- px = pState;
-
- /* Initialize pCoeffs pointer */
- pb = pCoeffs;
-
- /* Loop over numTaps number of values */
- tapCnt = numTaps;
-
- while(tapCnt > 0u)
- {
- /* Perform the multiply-accumulate */
- *pb = *pb + (w * (*px++));
- pb++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
- /* Advance state pointer by 1 for the next sample */
- pState = pState + 1;
-
- /* Decrement the loop counter */
- blkCnt--;
- }
-
-
- /* Processing is complete. Now copy the last numTaps - 1 samples to the
- * start of the state buffer. This prepares the state buffer for the
- * next function call. */
-
- /* Points to the start of the pState buffer */
- pStateCurnt = S->pState;
-
- /* Copy (numTaps - 1u) samples */
- tapCnt = (numTaps - 1u);
-
- /* Copy the data */
- while(tapCnt > 0u)
- {
- *pStateCurnt++ = *pState++;
-
- /* Decrement the loop counter */
- tapCnt--;
- }
-
-#endif /* #ifndef ARM_MATH_CM0_FAMILY */
-
-}
-
-/**
- * @} end of LMS group
- */
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