/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_biquad_cascade_df1_fast_q15.c
* Description: Fast processing function for the Q15 Biquad cascade filter
*
* $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"
/**
* @ingroup groupFilters
*/
/**
* @addtogroup BiquadCascadeDF1
* @{
*/
/**
* @details
* @param[in] *S points to an instance of the Q15 Biquad cascade structure.
* @param[in] *pSrc points to the block of input data.
* @param[out] *pDst points to the block of output data.
* @param[in] blockSize number of samples to process per call.
* @return none.
*
* Scaling and Overflow Behavior:
* \par
* This fast version uses a 32-bit accumulator with 2.30 format.
* The accumulator maintains full precision of the intermediate multiplication results but provides only a single guard bit.
* Thus, if the accumulator result overflows it wraps around and distorts the result.
* In order to avoid overflows completely the input signal must be scaled down by two bits and lie in the range [-0.25 +0.25).
* The 2.30 accumulator is then shifted by postShift bits and the result truncated to 1.15 format by discarding the low 16 bits.
*
* \par
* Refer to the function arm_biquad_cascade_df1_q15() for a slower implementation of this function which uses 64-bit accumulation to avoid wrap around distortion. Both the slow and the fast versions use the same instance structure.
* Use the function arm_biquad_cascade_df1_init_q15() to initialize the filter structure.
*
*/
void arm_biquad_cascade_df1_fast_q15(
const arm_biquad_casd_df1_inst_q15 * S,
q15_t * pSrc,
q15_t * pDst,
uint32_t blockSize)
{
q15_t *pIn = pSrc; /* Source pointer */
q15_t *pOut = pDst; /* Destination pointer */
q31_t in; /* Temporary variable to hold input value */
q31_t out; /* Temporary variable to hold output value */
q31_t b0; /* Temporary variable to hold bo value */
q31_t b1, a1; /* Filter coefficients */
q31_t state_in, state_out; /* Filter state variables */
q31_t acc; /* Accumulator */
int32_t shift = (int32_t) (15 - S->postShift); /* Post shift */
q15_t *pState = S->pState; /* State pointer */
q15_t *pCoeffs = S->pCoeffs; /* Coefficient pointer */
uint32_t sample, stage = S->numStages; /* Stage loop counter */
do
{
/* Read the b0 and 0 coefficients using SIMD */
b0 = *__SIMD32(pCoeffs)++;
/* Read the b1 and b2 coefficients using SIMD */
b1 = *__SIMD32(pCoeffs)++;
/* Read the a1 and a2 coefficients using SIMD */
a1 = *__SIMD32(pCoeffs)++;
/* Read the input state values from the state buffer: x[n-1], x[n-2] */
state_in = *__SIMD32(pState)++;
/* Read the output state values from the state buffer: y[n-1], y[n-2] */
state_out = *__SIMD32(pState)--;
/* Apply loop unrolling and compute 2 output values simultaneously. */
/* The variable acc hold output values that are being computed:
*
* acc = b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] + a1 * y[n-1] + a2 * y[n-2]
* acc = b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] + a1 * y[n-1] + a2 * y[n-2]
*/
sample = blockSize >> 1U;
/* First part of the processing with loop unrolling. Compute 2 outputs at a time.
** a second loop below computes the remaining 1 sample. */
while (sample > 0U)
{
/* Read the input */
in = *__SIMD32(pIn)++;
/* out = b0 * x[n] + 0 * 0 */
out = __SMUAD(b0, in);
/* acc = b1 * x[n-1] + acc += b2 * x[n-2] + out */
acc = __SMLAD(b1, state_in, out);
/* acc += a1 * y[n-1] + acc += a2 * y[n-2] */
acc = __SMLAD(a1, state_out, acc);
/* The result is converted from 3.29 to 1.31 and then saturation is applied */
out = __SSAT((acc >> shift), 16);
/* Every time after the output is computed state should be updated. */
/* The states should be updated as: */
/* Xn2 = Xn1 */
/* Xn1 = Xn */
/* Yn2 = Yn1 */
/* Yn1 = acc */
/* x[n-N], x[n-N-1] are packed together to make state_in of type q31 */
/* y[n-N], y[n-N-1] are packed together to make state_out of type q31 */
#ifndef ARM_MATH_BIG_ENDIAN
state_in = __PKHBT(in, state_in, 16);
state_out = __PKHBT(out, state_out, 16);
#else
state_in = __PKHBT(state_in >> 16, (in >> 16), 16);
state_out = __PKHBT(state_out >> 16, (out), 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* out = b0 * x[n] + 0 * 0 */
out = __SMUADX(b0, in);
/* acc0 = b1 * x[n-1] , acc0 += b2 * x[n-2] + out */
acc = __SMLAD(b1, state_in, out);
/* acc += a1 * y[n-1] + acc += a2 * y[n-2] */
acc = __SMLAD(a1, state_out, acc);
/* The result is converted from 3.29 to 1.31 and then saturation is applied */
out = __SSAT((acc >> shift), 16);
/* Store the output in the destination buffer. */
#ifndef ARM_MATH_BIG_ENDIAN
*__SIMD32(pOut)++ = __PKHBT(state_out, out, 16);
#else
*__SIMD32(pOut)++ = __PKHBT(out, state_out >> 16, 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Every time after the output is computed state should be updated. */
/* The states should be updated as: */
/* Xn2 = Xn1 */
/* Xn1 = Xn */
/* Yn2 = Yn1 */
/* Yn1 = acc */
/* x[n-N], x[n-N-1] are packed together to make state_in of type q31 */
/* y[n-N], y[n-N-1] are packed together to make state_out of type q31 */
#ifndef ARM_MATH_BIG_ENDIAN
state_in = __PKHBT(in >> 16, state_in, 16);
state_out = __PKHBT(out, state_out, 16);
#else
state_in = __PKHBT(state_in >> 16, in, 16);
state_out = __PKHBT(state_out >> 16, out, 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Decrement the loop counter */
sample--;
}
/* If the blockSize is not a multiple of 2, compute any remaining output samples here.
** No loop unrolling is used. */
if ((blockSize & 0x1U) != 0U)
{
/* Read the input */
in = *pIn++;
/* out = b0 * x[n] + 0 * 0 */
#ifndef ARM_MATH_BIG_ENDIAN
out = __SMUAD(b0, in);
#else
out = __SMUADX(b0, in);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* acc = b1 * x[n-1], acc += b2 * x[n-2] + out */
acc = __SMLAD(b1, state_in, out);
/* acc += a1 * y[n-1] + acc += a2 * y[n-2] */
acc = __SMLAD(a1, state_out, acc);
/* The result is converted from 3.29 to 1.31 and then saturation is applied */
out = __SSAT((acc >> shift), 16);
/* Store the output in the destination buffer. */
*pOut++ = (q15_t) out;
/* Every time after the output is computed state should be updated. */
/* The states should be updated as: */
/* Xn2 = Xn1 */
/* Xn1 = Xn */
/* Yn2 = Yn1 */
/* Yn1 = acc */
/* x[n-N], x[n-N-1] are packed together to make state_in of type q31 */
/* y[n-N], y[n-N-1] are packed together to make state_out of type q31 */
#ifndef ARM_MATH_BIG_ENDIAN
state_in = __PKHBT(in, state_in, 16);
state_out = __PKHBT(out, state_out, 16);
#else
state_in = __PKHBT(state_in >> 16, in, 16);
state_out = __PKHBT(state_out >> 16, out, 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
}
/* The first stage goes from the input buffer to the output buffer. */
/* Subsequent (numStages - 1) occur in-place in the output buffer */
pIn = pDst;
/* Reset the output pointer */
pOut = pDst;
/* Store the updated state variables back into the state array */
*__SIMD32(pState)++ = state_in;
*__SIMD32(pState)++ = state_out;
/* Decrement the loop counter */
stage--;
} while (stage > 0U);
}
/**
* @} end of BiquadCascadeDF1 group
*/