mirror of
https://github.com/portapack-mayhem/mayhem-firmware.git
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255 lines
5.8 KiB
C++
255 lines
5.8 KiB
C++
/*
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* Copyright (C) 2014 Jared Boone, ShareBrained Technology, Inc.
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*
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* This file is part of PortaPack.
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2, or (at your option)
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* any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; see the file COPYING. If not, write to
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* the Free Software Foundation, Inc., 51 Franklin Street,
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* Boston, MA 02110-1301, USA.
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*/
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#ifndef __DSP_DECIMATE_H__
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#define __DSP_DECIMATE_H__
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#include <cstdint>
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#include <array>
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#include <memory>
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#include <algorithm>
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#include "utility.hpp"
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#include "dsp_types.hpp"
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namespace dsp {
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namespace decimate {
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class Complex8DecimateBy2CIC3 {
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public:
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buffer_c16_t execute(
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buffer_c8_t src,
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buffer_c16_t dst
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);
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private:
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uint32_t _i1_i0 { 0 };
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uint32_t _q1_q0 { 0 };
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};
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class TranslateByFSOver4AndDecimateBy2CIC3 {
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public:
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buffer_c16_t execute(
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buffer_c8_t src,
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buffer_c16_t dst
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);
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private:
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uint32_t _q1_i0 { 0 };
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uint32_t _q0_i1 { 0 };
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};
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class DecimateBy2CIC3 {
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public:
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buffer_c16_t execute(
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buffer_c16_t src,
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buffer_c16_t dst
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);
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private:
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uint32_t _iq0 { 0 };
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uint32_t _iq1 { 0 };
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};
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class FIR64AndDecimateBy2Real {
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public:
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static constexpr size_t taps_count = 64;
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FIR64AndDecimateBy2Real(
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const std::array<int16_t, taps_count>& taps
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) : taps(taps)
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{
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}
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buffer_s16_t execute(
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buffer_s16_t src,
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buffer_s16_t dst
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);
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private:
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std::array<int16_t, taps_count + 2> z;
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const std::array<int16_t, taps_count>& taps;
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};
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class FIRAndDecimateComplex {
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public:
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using sample_t = complex16_t;
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using tap_t = complex16_t;
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using taps_t = tap_t[];
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/* NOTE! Current code makes an assumption that block of samples to be
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* processed will be a multiple of the taps_count.
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*/
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FIRAndDecimateComplex(
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) : taps_count_ { 0 },
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decimation_factor_ { 1 }
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{
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}
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template<typename T>
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void configure(
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const T& taps,
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const size_t decimation_factor
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) {
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samples_ = std::make_unique<samples_t>(taps.size());
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taps_reversed_ = std::make_unique<taps_t>(taps.size());
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taps_count_ = taps.size();
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decimation_factor_ = decimation_factor;
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std::reverse_copy(taps.cbegin(), taps.cend(), &taps_reversed_[0]);
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}
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buffer_c16_t execute(
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buffer_c16_t src,
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buffer_c16_t dst
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);
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private:
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using samples_t = sample_t[];
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std::unique_ptr<samples_t> samples_;
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std::unique_ptr<taps_t> taps_reversed_;
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size_t taps_count_;
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size_t decimation_factor_;
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};
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class DecimateBy2CIC4Real {
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public:
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buffer_s16_t execute(
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buffer_s16_t src,
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buffer_s16_t dst
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);
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private:
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int16_t z[5];
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};
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#if 0
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class DecimateBy2HBF5Complex {
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public:
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buffer_c16_t execute(
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buffer_c16_t const src,
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buffer_c16_t const dst
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);
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private:
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complex16_t z[11];
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};
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class DecimateBy2HBF7Complex {
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public:
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buffer_c16_t execute(
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buffer_c16_t const src,
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buffer_c16_t const dst
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);
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private:
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complex16_t z[11];
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};
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#endif
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/* From http://www.dspguru.com/book/export/html/3
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Here are several basic techniques to fake circular buffers:
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Split the calculation: You can split any FIR calculation into its "pre-wrap"
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and "post-wrap" parts. By splitting the calculation into these two parts, you
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essentially can do the circular logic only once, rather than once per tap.
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(See fir_double_z in FirAlgs.c above.)
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Duplicate the delay line: For a FIR with N taps, use a delay line of size 2N.
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Copy each sample to its proper location, as well as at location-plus-N.
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Therefore, the FIR calculation's MAC loop can be done on a flat buffer of N
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points, starting anywhere within the first set of N points. The second set of
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N delayed samples provides the "wrap around" comparable to a true circular
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buffer. (See fir_double_z in FirAlgs.c above.)
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Duplicate the coefficients: This is similar to the above, except that the
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duplication occurs in terms of the coefficients, not the delay line.
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Compared to the previous method, this has a calculation advantage of not
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having to store each incoming sample twice, and it also has a memory
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advantage when the same coefficient set will be used on multiple delay lines.
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(See fir_double_h in FirAlgs.c above.)
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Use block processing: In block processing, you use a delay line which is a
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multiple of the number of taps. You therefore only have to move the data
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once per block to implement the delay-line mechanism. When the block size
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becomes "large", the overhead of a moving the delay line once per block
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becomes negligible.
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*/
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#if 0
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template<size_t N>
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class FIRAndDecimateBy2Complex {
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public:
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FIR64AndDecimateBy2Complex(
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const std::array<int16_t, N>& taps
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) : taps { taps }
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{
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}
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buffer_c16_t execute(
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buffer_c16_t const src,
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buffer_c16_t const dst
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) {
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/* int16_t input (sample count "n" must be multiple of 4)
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* -> int16_t output, decimated by 2.
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* taps are normalized to 1 << 16 == 1.0.
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*/
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return { dst.p, src.count / 2 };
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}
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private:
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std::array<complex16_t, N> z;
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const std::array<int16_t, N>& taps;
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complex<int16_t> process_one(const size_t start_offset) {
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const auto split = &z[start_offset];
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const auto end = &z[z.size()];
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auto tap = &taps[0];
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complex<int32_t> t { 0, 0 };
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auto p = split;
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while(p < end) {
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const auto t = *(tap++);
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const auto c = *(p++);
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t.real += c.real * t;
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t.imag += c.imag * t;
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}
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p = &z[0];
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while(p < split) {
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const auto t = *(tap++);
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const auto c = *(p++);
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t.real += c.real * t;
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t.imag += c.imag * t;
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}
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return { t.real / 65536, t.imag / 65536 };
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}
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};
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#endif
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} /* namespace decimate */
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} /* namespace dsp */
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#endif/*__DSP_DECIMATE_H__*/
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