kopia lustrzana https://github.com/f4exb/sdrangel
1183 wiersze
28 KiB
C++
1183 wiersze
28 KiB
C++
/* emnr.c
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This file is part of a program that implements a Software-Defined Radio.
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Copyright (C) 2015 Warren Pratt, NR0V
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Copyright (C) 2024 Edouard Griffiths, F4EXB Adapted to SDRangel
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License
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as published by the Free Software Foundation; either version 2
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of the License, or (at your option) any later version.
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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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You should have received a copy of the GNU General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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The author can be reached by email at
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warren@wpratt.com
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*/
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#include <limits>
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#include "comm.hpp"
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#include "calculus.hpp"
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#include "emnr.hpp"
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#include "amd.hpp"
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#include "anr.hpp"
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#include "anf.hpp"
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#include "snba.hpp"
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#include "bandpass.hpp"
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namespace WDSP {
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EMNR::AE::AE(
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int _msize,
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const std::vector<double>& _lambda_y,
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double _zetaThresh,
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double _psi
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) :
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msize(_msize),
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lambda_y(_lambda_y),
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zetaThresh(_zetaThresh),
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psi(_psi)
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{
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nmask.resize(msize);
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}
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EMNR::NPS::NPS(
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int _incr,
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double _rate,
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int _msize,
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const std::vector<double>& _lambda_y,
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std::vector<double>& _lambda_d,
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double _alpha_pow,
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double _alpha_Pbar,
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double _epsH1
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) :
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incr(_incr),
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rate(_rate),
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msize(_msize),
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lambda_y(_lambda_y),
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lambda_d(_lambda_d),
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alpha_pow(_alpha_pow),
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alpha_Pbar(_alpha_Pbar),
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epsH1(_epsH1)
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{
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epsH1r = epsH1 / (1.0 + epsH1);
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sigma2N.resize(msize);
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PH1y.resize(msize);
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Pbar.resize(msize);
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EN2y.resize(msize);
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for (int i = 0; i < msize; i++)
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{
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sigma2N[i] = 0.5;
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Pbar[i] = 0.5;
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}
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}
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void EMNR::NPS::LambdaDs()
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{
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for (int k = 0; k < msize; k++)
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{
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PH1y[k] = 1.0 / (1.0 + (1.0 + epsH1) * exp (- epsH1r * lambda_y[k] / sigma2N[k]));
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Pbar[k] = alpha_Pbar * Pbar[k] + (1.0 - alpha_Pbar) * PH1y[k];
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if (Pbar[k] > 0.99)
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PH1y[k] = std::min (PH1y[k], 0.99);
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EN2y[k] = (1.0 - PH1y[k]) * lambda_y[k] + PH1y[k] * sigma2N[k];
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sigma2N[k] = alpha_pow * sigma2N[k] + (1.0 - alpha_pow) * EN2y[k];
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}
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std::copy(sigma2N.begin(), sigma2N.end(), lambda_d.begin());
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}
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const std::array<double, 18> EMNR::NP::DVals = { 1.0, 2.0, 5.0, 8.0, 10.0, 15.0, 20.0, 30.0, 40.0,
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60.0, 80.0, 120.0, 140.0, 160.0, 180.0, 220.0, 260.0, 300.0 };
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const std::array<double, 18> EMNR::NP::MVals = { 0.000, 0.260, 0.480, 0.580, 0.610, 0.668, 0.705, 0.762, 0.800,
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0.841, 0.865, 0.890, 0.900, 0.910, 0.920, 0.930, 0.935, 0.940 };
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EMNR::NP::NP(
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int _incr,
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double _rate,
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int _msize,
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std::vector<double>& _lambda_y,
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std::vector<double>& _lambda_d
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) :
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incr(_incr),
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rate(_rate),
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msize(_msize),
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lambda_y(_lambda_y),
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lambda_d(_lambda_d),
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invQeqMax(0.5),
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av(2.12)
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{
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double tau0 = -128.0 / 8000.0 / log(0.7);
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alphaCsmooth = exp(-incr / rate / tau0);
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double tau1 = -128.0 / 8000.0 / log(0.96);
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alphaMax = exp(-incr / rate / tau1);
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double tau2 = -128.0 / 8000.0 / log(0.7);
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alphaCmin = exp(-incr / rate / tau2);
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double tau3 = -128.0 / 8000.0 / log(0.3);
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alphaMin_max_value = exp(-incr / rate / tau3);
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snrq = -incr / (0.064 * rate);
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double tau4 = -128.0 / 8000.0 / log(0.8);
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betamax = exp(-incr / rate / tau4);
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Dtime = 8.0 * 12.0 * 128.0 / 8000.0;
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U = 8;
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V = (int)(0.5 + (Dtime * rate / (U * incr)));
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if (V < 4)
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V = 4;
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if ((U = (int)(0.5 + (Dtime * rate / (V * incr)))) < 1)
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U = 1;
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D = U * V;
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interpM(&MofD, D, 18, DVals, MVals);
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interpM(&MofV, V, 18, DVals, MVals);
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invQbar_points[0] = 0.03;
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invQbar_points[1] = 0.05;
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invQbar_points[2] = 0.06;
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invQbar_points[3] = std::numeric_limits<double>::max();
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double db;
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db = 10.0 * log10(8.0) / (12.0 * 128 / 8000);
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nsmax[0] = pow(10.0, db / 10.0 * V * incr / rate);
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db = 10.0 * log10(4.0) / (12.0 * 128 / 8000);
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nsmax[1] = pow(10.0, db / 10.0 * V * incr / rate);
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db = 10.0 * log10(2.0) / (12.0 * 128 / 8000);
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nsmax[2] = pow(10.0, db / 10.0 * V * incr / rate);
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db = 10.0 * log10(1.2) / (12.0 * 128 / 8000);
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nsmax[3] = pow(10.0, db / 10.0 * V * incr / rate);
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p.resize(msize);
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alphaOptHat.resize(msize);
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alphaHat.resize(msize);
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sigma2N.resize(msize);
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pbar.resize(msize);
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p2bar.resize(msize);
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Qeq.resize(msize);
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bmin.resize(msize);
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bmin_sub.resize(msize);
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k_mod.resize(msize);
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actmin.resize(msize);
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actmin_sub.resize(msize);
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lmin_flag.resize(msize);
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pmin_u.resize(msize);
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actminbuff.resize(U);
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for (int i = 0; i < U; i++) {
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actminbuff[i].resize(msize);
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}
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alphaC = 1.0;
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subwc = V;
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amb_idx = 0;
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for (int k = 0; k < msize; k++) {
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lambda_y[k] = 0.5;
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}
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std::copy(lambda_y.begin(), lambda_y.end(), p.begin());
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std::copy(lambda_y.begin(), lambda_y.end(), sigma2N.begin());
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std::copy(lambda_y.begin(), lambda_y.end(), pbar.begin());
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std::copy(lambda_y.begin(), lambda_y.end(), pmin_u.begin());
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for (int k = 0; k < msize; k++)
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{
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p2bar[k] = lambda_y[k] * lambda_y[k];
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actmin[k] = std::numeric_limits<double>::max();
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actmin_sub[k] = std::numeric_limits<double>::max();
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for (int ku = 0; ku < U; ku++) {
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actminbuff[ku][k] = std::numeric_limits<double>::max();
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}
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}
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std::fill(lmin_flag.begin(), lmin_flag.end(), 0);
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}
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void EMNR::NP::interpM (
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double* res,
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double x,
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int nvals,
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const std::array<double, 18>& xvals,
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const std::array<double, 18>& yvals
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)
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{
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if (x <= xvals[0])
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{
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*res = yvals[0];
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}
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else if (x >= xvals[nvals - 1])
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{
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*res = yvals[nvals - 1];
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}
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else
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{
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int idx = 1;
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double xllow;
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double xlhigh;
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double frac;
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while ((x >= xvals[idx]) && (idx < nvals - 1))
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idx++;
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xllow = log10 (xvals[idx - 1]);
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xlhigh = log10(xvals[idx]);
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frac = (log10 (x) - xllow) / (xlhigh - xllow);
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*res = yvals[idx - 1] + frac * (yvals[idx] - yvals[idx - 1]);
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}
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}
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void EMNR::NP::LambdaD()
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{
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int k;
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double f0;
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double f1;
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double f2;
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double f3;
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double sum_prev_p;
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double sum_lambda_y;
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double alphaCtilda;
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double sum_prev_sigma2N;
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double alphaMin;
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double SNR;
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double beta;
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double varHat;
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double invQeq;
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double invQbar;
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double bc;
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double QeqTilda;
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double QeqTildaSub;
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double noise_slope_max;
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sum_prev_p = 0.0;
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sum_lambda_y = 0.0;
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sum_prev_sigma2N = 0.0;
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for (k = 0; k < msize; k++)
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{
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sum_prev_p += p[k];
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sum_lambda_y += lambda_y[k];
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sum_prev_sigma2N += sigma2N[k];
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}
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for (k = 0; k < msize; k++)
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{
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f0 = p[k] / sigma2N[k] - 1.0;
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alphaOptHat[k] = 1.0 / (1.0 + f0 * f0);
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}
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SNR = sum_prev_p / sum_prev_sigma2N;
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alphaMin = std::min (alphaMin_max_value, pow (SNR, snrq));
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for (k = 0; k < msize; k++)
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if (alphaOptHat[k] < alphaMin) alphaOptHat[k] = alphaMin;
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f1 = sum_prev_p / sum_lambda_y - 1.0;
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alphaCtilda = 1.0 / (1.0 + f1 * f1);
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alphaC = alphaCsmooth * alphaC + (1.0 - alphaCsmooth) * std::max (alphaCtilda, alphaCmin);
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f2 = alphaMax * alphaC;
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for (k = 0; k < msize; k++)
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alphaHat[k] = f2 * alphaOptHat[k];
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for (k = 0; k < msize; k++)
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p[k] = alphaHat[k] * p[k] + (1.0 - alphaHat[k]) * lambda_y[k];
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invQbar = 0.0;
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for (k = 0; k < msize; k++)
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{
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beta = std::min (betamax, alphaHat[k] * alphaHat[k]);
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pbar[k] = beta * pbar[k] + (1.0 - beta) * p[k];
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p2bar[k] = beta * p2bar[k] + (1.0 - beta) * p[k] * p[k];
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varHat = p2bar[k] - pbar[k] * pbar[k];
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invQeq = varHat / (2.0 * sigma2N[k] * sigma2N[k]);
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if (invQeq > invQeqMax)
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invQeq = invQeqMax;
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Qeq[k] = 1.0 / invQeq;
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invQbar += invQeq;
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}
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invQbar /= (double) msize;
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bc = 1.0 + av * sqrt (invQbar);
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for (k = 0; k < msize; k++)
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{
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QeqTilda = (Qeq[k] - 2.0 * MofD) / (1.0 - MofD);
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QeqTildaSub = (Qeq[k] - 2.0 * MofV) / (1.0 - MofV);
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bmin[k] = 1.0 + 2.0 * (D - 1.0) / QeqTilda;
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bmin_sub[k] = 1.0 + 2.0 * (V - 1.0) / QeqTildaSub;
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}
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std::fill(k_mod.begin(), k_mod.end(), 0);
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for (k = 0; k < msize; k++)
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{
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f3 = p[k] * bmin[k] * bc;
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if (f3 < actmin[k])
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{
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actmin[k] = f3;
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actmin_sub[k] = p[k] * bmin_sub[k] * bc;
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k_mod[k] = 1;
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}
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}
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if (subwc == V)
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{
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if (invQbar < invQbar_points[0])
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noise_slope_max = nsmax[0];
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else if (invQbar < invQbar_points[1])
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noise_slope_max = nsmax[1];
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else if (invQbar < invQbar_points[2])
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noise_slope_max = nsmax[2];
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else
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noise_slope_max = nsmax[3];
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for (k = 0; k < msize; k++)
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{
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int ku;
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double min;
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if (k_mod[k])
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lmin_flag[k] = 0;
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actminbuff[amb_idx][k] = actmin[k];
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min = std::numeric_limits<double>::max();
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for (ku = 0; ku < U; ku++)
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{
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if (actminbuff[ku][k] < min)
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min = actminbuff[ku][k];
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}
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pmin_u[k] = min;
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if ((lmin_flag[k] == 1)
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&& (actmin_sub[k] < noise_slope_max * pmin_u[k])
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&& (actmin_sub[k] > pmin_u[k]))
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{
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pmin_u[k] = actmin_sub[k];
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for (ku = 0; ku < U; ku++)
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actminbuff[ku][k] = actmin_sub[k];
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}
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lmin_flag[k] = 0;
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actmin[k] = std::numeric_limits<double>::max();
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actmin_sub[k] = std::numeric_limits<double>::max();
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}
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if (++amb_idx == U)
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amb_idx = 0;
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subwc = 1;
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}
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else
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{
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if (subwc > 1)
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{
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for (k = 0; k < msize; k++)
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{
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if (k_mod[k])
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{
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lmin_flag[k] = 1;
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sigma2N[k] = std::min (actmin_sub[k], pmin_u[k]);
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pmin_u[k] = sigma2N[k];
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}
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}
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}
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++subwc;
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}
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std::copy(sigma2N.begin(), sigma2N.end(), lambda_d.begin());
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}
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EMNR::G::G(
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int _incr,
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double _rate,
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int _msize,
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std::vector<double>& _mask,
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const std::vector<float>& _y
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) :
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incr(_incr),
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rate(_rate),
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msize(_msize),
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mask(_mask),
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y(_y)
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{
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lambda_y.resize(msize);
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lambda_d.resize(msize);
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prev_gamma.resize(msize);
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prev_mask.resize(msize);
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gf1p5 = sqrt(PI) / 2.0;
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double tau = -128.0 / 8000.0 / log(0.98);
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alpha = exp(-incr / rate / tau);
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eps_floor = std::numeric_limits<double>::min();
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gamma_max = 1000.0;
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q = 0.2;
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std::fill(prev_mask.begin(), prev_mask.end(), 1.0);
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std::fill(prev_gamma.begin(), prev_gamma.end(), 1.0);
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gmax = 10000.0;
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std::copy(Calculus::GG.begin(), Calculus::GG.end(), GG.begin());
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std::copy(Calculus::GGS.begin(), Calculus::GGS.end(), GGS.begin());
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// We keep this pretty useless part just in case...
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if ((fileb = fopen("calculus", "rb")))
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{
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std::array<double, 241*241> gg;
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std::size_t lgg = fread(&gg[0], sizeof(double), 241 * 241, fileb);
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if (lgg != 241 * 241) {
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fprintf(stderr, "GG file has an invalid size\n");
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} else {
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std::copy(gg.begin(), gg.end(), GG.begin());
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}
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std::array<double, 241*241> ggs;
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std::size_t lggs =fread(&ggs[0], sizeof(double), 241 * 241, fileb);
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if (lggs != 241 * 241) {
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fprintf(stderr, "GGS file has an invalid size\n");
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} else {
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std::copy(ggs.begin(), ggs.end(), GGS.begin());
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}
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fclose(fileb);
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}
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}
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void EMNR::G::calc_gamma0()
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{
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double gamma;
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double eps_hat;
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double v;
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for (int k = 0; k < msize; k++)
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{
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gamma = std::min (lambda_y[k] / lambda_d[k], gamma_max);
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eps_hat = alpha * prev_mask[k] * prev_mask[k] * prev_gamma[k]
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+ (1.0 - alpha) * std::max (gamma - 1.0f, eps_floor);
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v = (eps_hat / (1.0 + eps_hat)) * gamma;
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mask[k] = gf1p5 * sqrt (v) / gamma * exp (- 0.5 * v)
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* ((1.0 + v) * bessI0 (0.5 * v) + v * bessI1 (0.5 * v));
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double v2 = std::min (v, 700.0);
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double eta = mask[k] * mask[k] * lambda_y[k] / lambda_d[k];
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|
double eps = eta / (1.0 - q);
|
|
double witchHat = (1.0 - q) / q * exp (v2) / (1.0 + eps);
|
|
mask[k] *= witchHat / (1.0 + witchHat);
|
|
|
|
if (mask[k] > gmax)
|
|
mask[k] = gmax;
|
|
|
|
prev_gamma[k] = gamma;
|
|
prev_mask[k] = mask[k];
|
|
}
|
|
}
|
|
|
|
void EMNR::G::calc_gamma1()
|
|
{
|
|
double gamma;
|
|
double eps_hat;
|
|
double v;
|
|
double ehr;
|
|
|
|
for (int k = 0; k < msize; k++)
|
|
{
|
|
gamma = std::min (lambda_y[k] / lambda_d[k], gamma_max);
|
|
eps_hat = alpha * prev_mask[k] * prev_mask[k] * prev_gamma[k]
|
|
+ (1.0 - alpha) * std::max (gamma - 1.0f, eps_floor);
|
|
ehr = eps_hat / (1.0 + eps_hat);
|
|
v = ehr * gamma;
|
|
|
|
if ((mask[k] = ehr * exp (std::min (700.0, 0.5 * e1xb(v)))) > gmax)
|
|
mask[k] = gmax;
|
|
|
|
prev_gamma[k] = gamma;
|
|
prev_mask[k] = mask[k];
|
|
}
|
|
}
|
|
|
|
void EMNR::G::calc_gamma2()
|
|
{
|
|
double gamma;
|
|
double eps_hat;
|
|
double eps_p;
|
|
|
|
for (int k = 0; k < msize; k++)
|
|
{
|
|
gamma = std::min(lambda_y[k] / lambda_d[k], gamma_max);
|
|
eps_hat = alpha * prev_mask[k] * prev_mask[k] * prev_gamma[k]
|
|
+ (1.0 - alpha) * std::max(gamma - 1.0f, eps_floor);
|
|
eps_p = eps_hat / (1.0 - q);
|
|
mask[k] = getKey(GG, gamma, eps_hat) * getKey(GGS, gamma, eps_p);
|
|
prev_gamma[k] = gamma;
|
|
prev_mask[k] = mask[k];
|
|
}
|
|
}
|
|
|
|
void EMNR::G::calc_lambda_y()
|
|
{
|
|
for (int k = 0; k < msize; k++)
|
|
{
|
|
double y0 = y[2 * k + 0];
|
|
double y1 = y[2 * k + 1];
|
|
lambda_y[k] = y0 * y0 + y1 * y1;
|
|
}
|
|
}
|
|
|
|
/********************************************************************************************************
|
|
* *
|
|
* Special Functions *
|
|
* *
|
|
********************************************************************************************************/
|
|
|
|
// MODIFIED BESSEL FUNCTIONS OF THE 0TH AND 1ST ORDERS, Polynomial Approximations
|
|
// M. Abramowitz and I. Stegun, Eds., "Handbook of Mathematical Functions." Washington, DC: National
|
|
// Bureau of Standards, 1964.
|
|
// Shanjie Zhang and Jianming Jin, "Computation of Special Functions." New York, NY, John Wiley and Sons,
|
|
// Inc., 1996. [Sample code given in FORTRAN]
|
|
|
|
double EMNR::G::bessI0 (double x)
|
|
{
|
|
double res;
|
|
double p;
|
|
|
|
if (x == 0.0)
|
|
{
|
|
res = 1.0;
|
|
}
|
|
else
|
|
{
|
|
if (x < 0.0)
|
|
x = -x;
|
|
|
|
if (x <= 3.75)
|
|
{
|
|
p = x / 3.75;
|
|
p = p * p;
|
|
res = ((((( 0.0045813 * p
|
|
+ 0.0360768) * p
|
|
+ 0.2659732) * p
|
|
+ 1.2067492) * p
|
|
+ 3.0899424) * p
|
|
+ 3.5156229) * p
|
|
+ 1.0;
|
|
}
|
|
else
|
|
{
|
|
p = 3.75 / x;
|
|
res = exp (x) / sqrt (x)
|
|
* (((((((( + 0.00392377 * p
|
|
- 0.01647633) * p
|
|
+ 0.02635537) * p
|
|
- 0.02057706) * p
|
|
+ 0.00916281) * p
|
|
- 0.00157565) * p
|
|
+ 0.00225319) * p
|
|
+ 0.01328592) * p
|
|
+ 0.39894228);
|
|
}
|
|
}
|
|
return res;
|
|
}
|
|
|
|
double EMNR::G::bessI1 (double x)
|
|
{
|
|
|
|
double res;
|
|
double p;
|
|
|
|
if (x == 0.0)
|
|
{
|
|
res = 0.0;
|
|
}
|
|
else
|
|
{
|
|
if (x < 0.0)
|
|
x = -x;
|
|
|
|
if (x <= 3.75)
|
|
{
|
|
p = x / 3.75;
|
|
p = p * p;
|
|
res = x
|
|
* (((((( 0.00032411 * p
|
|
+ 0.00301532) * p
|
|
+ 0.02658733) * p
|
|
+ 0.15084934) * p
|
|
+ 0.51498869) * p
|
|
+ 0.87890594) * p
|
|
+ 0.5);
|
|
}
|
|
else
|
|
{
|
|
p = 3.75 / x;
|
|
res = exp (x) / sqrt (x)
|
|
* (((((((( - 0.00420059 * p
|
|
+ 0.01787654) * p
|
|
- 0.02895312) * p
|
|
+ 0.02282967) * p
|
|
- 0.01031555) * p
|
|
+ 0.00163801) * p
|
|
- 0.00362018) * p
|
|
- 0.03988024) * p
|
|
+ 0.39894228);
|
|
}
|
|
}
|
|
|
|
return res;
|
|
}
|
|
|
|
// EXPONENTIAL INTEGRAL, E1(x)
|
|
// M. Abramowitz and I. Stegun, Eds., "Handbook of Mathematical Functions." Washington, DC: National
|
|
// Bureau of Standards, 1964.
|
|
// Shanjie Zhang and Jianming Jin, "Computation of Special Functions." New York, NY, John Wiley and Sons,
|
|
// Inc., 1996. [Sample code given in FORTRAN]
|
|
|
|
double EMNR::G::e1xb (double x)
|
|
{
|
|
double e1;
|
|
double ga;
|
|
double r;
|
|
double t;
|
|
double t0;
|
|
int k;
|
|
int m;
|
|
|
|
if (x == 0.0)
|
|
{
|
|
e1 = std::numeric_limits<double>::max();
|
|
}
|
|
else if (x <= 1.0)
|
|
{
|
|
e1 = 1.0;
|
|
r = 1.0;
|
|
|
|
for (k = 1; k <= 25; k++)
|
|
{
|
|
r = -r * k * x / ((k + 1.0)*(k + 1.0));
|
|
e1 = e1 + r;
|
|
|
|
if ( fabs (r) <= fabs (e1) * 1.0e-15 )
|
|
break;
|
|
}
|
|
|
|
ga = 0.5772156649015328;
|
|
e1 = - ga - log (x) + x * e1;
|
|
}
|
|
else
|
|
{
|
|
m = 20 + (int)(80.0 / x);
|
|
t0 = 0.0;
|
|
|
|
for (k = m; k >= 1; k--)
|
|
t0 = (float)k / (1.0 + k / (x + t0));
|
|
|
|
t = 1.0 / (x + t0);
|
|
e1 = exp (- x) * t;
|
|
}
|
|
|
|
return e1;
|
|
}
|
|
|
|
/********************************************************************************************************
|
|
* *
|
|
* Main Body of Code *
|
|
* *
|
|
********************************************************************************************************/
|
|
|
|
void EMNR::calc_window()
|
|
{
|
|
int i;
|
|
double arg;
|
|
double sum;
|
|
double inv_coherent_gain;
|
|
|
|
if (wintype == 0)
|
|
{
|
|
arg = 2.0 * PI / (double) fsize;
|
|
sum = 0.0;
|
|
|
|
for (i = 0; i < fsize; i++)
|
|
{
|
|
window[i] = (float) (sqrt (0.54 - 0.46 * cos((float)i * arg)));
|
|
sum += window[i];
|
|
}
|
|
|
|
inv_coherent_gain = (double) fsize / sum;
|
|
|
|
for (i = 0; i < fsize; i++)
|
|
window[i] *= (float) inv_coherent_gain;
|
|
}
|
|
}
|
|
|
|
void EMNR::calc()
|
|
{
|
|
// float Hvals[18] = { 0.000, 0.150, 0.480, 0.780, 0.980, 1.550, 2.000, 2.300, 2.520,
|
|
// 3.100, 3.380, 4.150, 4.350, 4.250, 3.900, 4.100, 4.700, 5.000 };
|
|
incr = fsize / ovrlp;
|
|
gain = ogain / fsize / (float)ovrlp;
|
|
|
|
if (fsize > bsize)
|
|
iasize = fsize;
|
|
else
|
|
iasize = bsize + fsize - incr;
|
|
|
|
iainidx = 0;
|
|
iaoutidx = 0;
|
|
|
|
if (fsize > bsize)
|
|
{
|
|
if (bsize > incr)
|
|
oasize = bsize;
|
|
else
|
|
oasize = incr;
|
|
|
|
oainidx = (fsize - bsize - incr) % oasize;
|
|
}
|
|
else
|
|
{
|
|
oasize = bsize;
|
|
oainidx = fsize - incr;
|
|
}
|
|
|
|
init_oainidx = oainidx;
|
|
oaoutidx = 0;
|
|
msize = fsize / 2 + 1;
|
|
window.resize(fsize);
|
|
inaccum.resize(iasize);
|
|
forfftin.resize(fsize);
|
|
forfftout.resize(msize * 2);
|
|
mask.resize(msize);
|
|
std::fill(mask.begin(), mask.end(), 1.0);
|
|
revfftin.resize(msize * 2);
|
|
revfftout.resize(fsize);
|
|
save.resize(ovrlp);
|
|
|
|
for (int i = 0; i < ovrlp; i++)
|
|
save[i].resize(fsize);
|
|
|
|
outaccum.resize(oasize);
|
|
nsamps = 0;
|
|
saveidx = 0;
|
|
Rfor = fftwf_plan_dft_r2c_1d(
|
|
fsize,
|
|
forfftin.data(),
|
|
(fftwf_complex *)forfftout.data(),
|
|
FFTW_ESTIMATE
|
|
);
|
|
Rrev = fftwf_plan_dft_c2r_1d(
|
|
fsize,
|
|
(fftwf_complex *)revfftin.data(),
|
|
revfftout.data(),
|
|
FFTW_ESTIMATE
|
|
);
|
|
|
|
calc_window();
|
|
|
|
// G
|
|
|
|
g = new G(
|
|
incr,
|
|
rate,
|
|
msize,
|
|
mask,
|
|
forfftout
|
|
);
|
|
|
|
// NP
|
|
|
|
np = new NP(
|
|
incr,
|
|
rate,
|
|
msize,
|
|
g->lambda_y,
|
|
g->lambda_d
|
|
);
|
|
|
|
// NPS
|
|
|
|
double tauNPS0 = -128.0 / 8000.0 / log(0.8);
|
|
double alpha_pow = exp(-incr / rate / tauNPS0);
|
|
|
|
double tauNPS1 = -128.0 / 8000.0 / log(0.9);
|
|
double alpha_Pbar = exp(-incr / rate / tauNPS1);
|
|
|
|
nps = new NPS(
|
|
incr,
|
|
rate,
|
|
msize,
|
|
g->lambda_y,
|
|
g->lambda_d,
|
|
alpha_pow,
|
|
alpha_Pbar,
|
|
pow(10.0, 15.0 / 10.0) // epsH1
|
|
);
|
|
|
|
// AE
|
|
|
|
ae = new AE(
|
|
msize,
|
|
g->lambda_y,
|
|
0.75, // zetaThresh
|
|
10.0 // psi
|
|
);
|
|
}
|
|
|
|
void EMNR::decalc()
|
|
{
|
|
delete ae;
|
|
delete nps;
|
|
delete np;
|
|
delete g;
|
|
|
|
fftwf_destroy_plan(Rrev);
|
|
fftwf_destroy_plan(Rfor);
|
|
}
|
|
|
|
EMNR::EMNR(
|
|
int _run,
|
|
int _position,
|
|
int _size,
|
|
float* _in,
|
|
float* _out,
|
|
int _fsize,
|
|
int _ovrlp,
|
|
int _rate,
|
|
int _wintype,
|
|
double _gain,
|
|
int _gain_method,
|
|
int _npe_method,
|
|
int _ae_run
|
|
)
|
|
{
|
|
run = _run;
|
|
position = _position;
|
|
bsize = _size;
|
|
in = _in;
|
|
out = _out;
|
|
fsize = _fsize;
|
|
ovrlp = _ovrlp;
|
|
rate = _rate;
|
|
wintype = _wintype;
|
|
ogain = _gain;
|
|
calc();
|
|
g->gain_method = _gain_method;
|
|
g->npe_method = _npe_method;
|
|
g->ae_run = _ae_run;
|
|
}
|
|
|
|
void EMNR::flush()
|
|
{
|
|
std::fill(inaccum.begin(), inaccum.end(), 0);
|
|
|
|
for (int i = 0; i < ovrlp; i++)
|
|
std::fill(save[i].begin(), save[i].end(), 0);
|
|
|
|
std::fill(outaccum.begin(), outaccum.end(), 0);
|
|
nsamps = 0;
|
|
iainidx = 0;
|
|
iaoutidx = 0;
|
|
oainidx = init_oainidx;
|
|
oaoutidx = 0;
|
|
saveidx = 0;
|
|
}
|
|
|
|
EMNR::~EMNR()
|
|
{
|
|
decalc();
|
|
}
|
|
|
|
void EMNR::aepf()
|
|
{
|
|
int k;
|
|
int N;
|
|
int n;
|
|
double sumPre;
|
|
double sumPost;
|
|
double zeta;
|
|
double zetaT;
|
|
sumPre = 0.0;
|
|
sumPost = 0.0;
|
|
|
|
for (k = 0; k < ae->msize; k++)
|
|
{
|
|
sumPre += ae->lambda_y[k];
|
|
sumPost += mask[k] * mask[k] * ae->lambda_y[k];
|
|
}
|
|
|
|
zeta = sumPost / sumPre;
|
|
|
|
if (zeta >= ae->zetaThresh)
|
|
zetaT = 1.0;
|
|
else
|
|
zetaT = zeta;
|
|
|
|
if (zetaT == 1.0)
|
|
N = 1;
|
|
else
|
|
N = 1 + 2 * (int)(0.5 + ae->psi * (1.0 - zetaT / ae->zetaThresh));
|
|
|
|
n = N / 2;
|
|
|
|
for (k = n; k < (ae->msize - n); k++)
|
|
{
|
|
ae->nmask[k] = 0.0;
|
|
for (int m = k - n; m <= (k + n); m++)
|
|
ae->nmask[k] += mask[m];
|
|
ae->nmask[k] /= (float)N;
|
|
}
|
|
|
|
std::copy(ae->nmask.begin(), ae->nmask.end() - 2*n, &mask[n]);
|
|
}
|
|
|
|
double EMNR::G::getKey(const std::array<double, 241*241>& type, double gamma, double xi)
|
|
{
|
|
int ngamma1;
|
|
int ngamma2;
|
|
int nxi1 = 0;
|
|
int nxi2 = 0;
|
|
double tg;
|
|
double tx;
|
|
double dg;
|
|
double dx;
|
|
const double dmin = 0.001;
|
|
const double dmax = 1000.0;
|
|
|
|
if (gamma <= dmin)
|
|
{
|
|
ngamma1 = ngamma2 = 0;
|
|
tg = 0.0;
|
|
}
|
|
else if (gamma >= dmax)
|
|
{
|
|
ngamma1 = ngamma2 = 240;
|
|
tg = 60.0;
|
|
}
|
|
else
|
|
{
|
|
tg = 10.0 * log10(gamma / dmin);
|
|
ngamma1 = (int)(4.0 * tg);
|
|
ngamma2 = ngamma1 + 1;
|
|
}
|
|
|
|
if (xi <= dmin)
|
|
{
|
|
nxi1 = nxi2 = 0;
|
|
tx = 0.0;
|
|
}
|
|
else if (xi >= dmax)
|
|
{
|
|
nxi1 = nxi2 = 240;
|
|
tx = 60.0;
|
|
}
|
|
else
|
|
{
|
|
tx = 10.0 * log10(xi / dmin);
|
|
nxi1 = (int)(4.0 * tx);
|
|
nxi2 = nxi1 + 1;
|
|
}
|
|
|
|
dg = (tg - 0.25 * ngamma1) / 0.25;
|
|
dx = (tx - 0.25 * nxi1) / 0.25;
|
|
|
|
std::array<int, 4> ix;
|
|
ix[0] = 241 * nxi1 + ngamma1;
|
|
ix[1] = 241 * nxi2 + ngamma1;
|
|
ix[2] = 241 * nxi1 + ngamma2;
|
|
ix[3] = 241 * nxi2 + ngamma2;
|
|
|
|
for (auto& ixi : ix)
|
|
{
|
|
if (ixi < 0) {
|
|
ixi = 0;
|
|
} else if (ixi >= 241*241) {
|
|
ixi = 241*241 - 1;
|
|
}
|
|
}
|
|
|
|
return (1.0 - dg) * (1.0 - dx) * type[ix[0]]
|
|
+ (1.0 - dg) * dx * type[ix[1]]
|
|
+ dg * (1.0 - dx) * type[ix[2]]
|
|
+ dg * dx * type[ix[3]];
|
|
}
|
|
|
|
void EMNR::calc_gain()
|
|
{
|
|
g->calc_lambda_y();
|
|
|
|
switch (g->npe_method)
|
|
{
|
|
case 0:
|
|
np->LambdaD();
|
|
break;
|
|
case 1:
|
|
nps->LambdaDs();
|
|
break;
|
|
default:
|
|
break;
|
|
}
|
|
|
|
switch (g->gain_method)
|
|
{
|
|
case 0:
|
|
g->calc_gamma0();
|
|
break;
|
|
case 1:
|
|
g->calc_gamma1();
|
|
break;
|
|
case 2:
|
|
g->calc_gamma2();
|
|
break;
|
|
default:
|
|
break;
|
|
}
|
|
|
|
if (g->ae_run)
|
|
aepf();
|
|
}
|
|
|
|
void EMNR::execute(int _pos)
|
|
{
|
|
if (run && _pos == position)
|
|
{
|
|
int i;
|
|
int j;
|
|
int k;
|
|
int sbuff;
|
|
int sbegin;
|
|
double g1;
|
|
|
|
for (i = 0; i < 2 * bsize; i += 2)
|
|
{
|
|
inaccum[iainidx] = in[i];
|
|
iainidx = (iainidx + 1) % iasize;
|
|
}
|
|
|
|
nsamps += bsize;
|
|
|
|
while (nsamps >= fsize)
|
|
{
|
|
for (i = 0, j = iaoutidx; i < fsize; i++, j = (j + 1) % iasize)
|
|
forfftin[i] = window[i] * inaccum[j];
|
|
|
|
iaoutidx = (iaoutidx + incr) % iasize;
|
|
nsamps -= incr;
|
|
fftwf_execute (Rfor);
|
|
calc_gain();
|
|
|
|
for (i = 0; i < msize; i++)
|
|
{
|
|
g1 = gain * mask[i];
|
|
revfftin[2 * i + 0] = (float) (g1 * forfftout[2 * i + 0]);
|
|
revfftin[2 * i + 1] = (float) (g1 * forfftout[2 * i + 1]);
|
|
}
|
|
|
|
fftwf_execute (Rrev);
|
|
|
|
for (i = 0; i < fsize; i++)
|
|
save[saveidx][i] = window[i] * revfftout[i];
|
|
|
|
for (i = ovrlp; i > 0; i--)
|
|
{
|
|
sbuff = (saveidx + i) % ovrlp;
|
|
sbegin = incr * (ovrlp - i);
|
|
|
|
for (j = sbegin, k = oainidx; j < incr + sbegin; j++, k = (k + 1) % oasize)
|
|
{
|
|
if ( i == ovrlp)
|
|
outaccum[k] = save[sbuff][j];
|
|
else
|
|
outaccum[k] += save[sbuff][j];
|
|
}
|
|
}
|
|
|
|
saveidx = (saveidx + 1) % ovrlp;
|
|
oainidx = (oainidx + incr) % oasize;
|
|
}
|
|
|
|
for (i = 0; i < bsize; i++)
|
|
{
|
|
out[2 * i + 0] = outaccum[oaoutidx];
|
|
out[2 * i + 1] = 0.0;
|
|
oaoutidx = (oaoutidx + 1) % oasize;
|
|
}
|
|
}
|
|
else if (out != in)
|
|
{
|
|
std::copy(in, in + bsize * 2, out);
|
|
}
|
|
}
|
|
|
|
void EMNR::setBuffers(float* _in, float* _out)
|
|
{
|
|
in = _in;
|
|
out = _out;
|
|
}
|
|
|
|
void EMNR::setSamplerate(int _rate)
|
|
{
|
|
decalc();
|
|
rate = _rate;
|
|
calc();
|
|
}
|
|
|
|
void EMNR::setSize(int _size)
|
|
{
|
|
decalc();
|
|
bsize = _size;
|
|
calc();
|
|
}
|
|
|
|
/********************************************************************************************************
|
|
* *
|
|
* RXA Properties *
|
|
* *
|
|
********************************************************************************************************/
|
|
|
|
void EMNR::setGainMethod(int _method)
|
|
{
|
|
g->gain_method = _method;
|
|
}
|
|
|
|
void EMNR::setNpeMethod(int _method)
|
|
{
|
|
g->npe_method = _method;
|
|
}
|
|
|
|
void EMNR::setAeRun(int _run)
|
|
{
|
|
g->ae_run = _run;
|
|
}
|
|
|
|
void EMNR::setAeZetaThresh(double _zetathresh)
|
|
{
|
|
ae->zetaThresh = _zetathresh;
|
|
}
|
|
|
|
void EMNR::setAePsi(double _psi)
|
|
{
|
|
ae->psi = _psi;
|
|
}
|
|
|
|
} // namespace WDSP
|