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7cb15bbd95
sdrangel/wdsp/emnr.cpp
f4exb 7cb15bbd95 WDSP: EMNR rework
2024-07-29 20:12:44 +02:00

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/* emnr.c
This file is part of a program that implements a Software-Defined Radio.
Copyright (C) 2015 Warren Pratt, NR0V
Copyright (C) 2024 Edouard Griffiths, F4EXB Adapted to SDRangel
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
The author can be reached by email at
warren@wpratt.com
*/
#include <limits>
#include "comm.hpp"
#include "calculus.hpp"
#include "emnr.hpp"
#include "amd.hpp"
#include "anr.hpp"
#include "anf.hpp"
#include "snba.hpp"
#include "bandpass.hpp"
#include "RXA.hpp"
namespace WDSP {
EMNR::AE::AE(
int _msize,
const std::vector<double>& _lambda_y,
double _zetaThresh,
double _psi
) :
msize(_msize),
lambda_y(_lambda_y),
zetaThresh(_zetaThresh),
psi(_psi)
{
nmask.resize(msize);
}
EMNR::NPS::NPS(
int _incr,
double _rate,
int _msize,
const std::vector<double>& _lambda_y,
std::vector<double>& _lambda_d,
double _alpha_pow,
double _alpha_Pbar,
double _epsH1
) :
incr(_incr),
rate(_rate),
msize(_msize),
lambda_y(_lambda_y),
lambda_d(_lambda_d),
alpha_pow(_alpha_pow),
alpha_Pbar(_alpha_Pbar),
epsH1(_epsH1)
{
epsH1r = epsH1 / (1.0 + epsH1);
sigma2N.resize(msize); // (float *)malloc0(nps.msize * sizeof(float));
PH1y.resize(msize); // (float *)malloc0(nps.msize * sizeof(float));
Pbar.resize(msize); // (float *)malloc0(nps.msize * sizeof(float));
EN2y.resize(msize); // (float *)malloc0(nps.msize * sizeof(float));
for (int i = 0; i < msize; i++)
{
sigma2N[i] = 0.5;
Pbar[i] = 0.5;
}
}
void EMNR::NPS::LambdaDs()
{
int k;
for (k = 0; k < msize; k++)
{
PH1y[k] = 1.0 / (1.0 + (1.0 + epsH1) * exp (- epsH1r * lambda_y[k] / sigma2N[k]));
Pbar[k] = alpha_Pbar * Pbar[k] + (1.0 - alpha_Pbar) * PH1y[k];
if (Pbar[k] > 0.99)
PH1y[k] = std::min (PH1y[k], 0.99);
EN2y[k] = (1.0 - PH1y[k]) * lambda_y[k] + PH1y[k] * sigma2N[k];
sigma2N[k] = alpha_pow * sigma2N[k] + (1.0 - alpha_pow) * EN2y[k];
}
std::copy(sigma2N.begin(), sigma2N.end(), lambda_d.begin());
}
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,
60.0, 80.0, 120.0, 140.0, 160.0, 180.0, 220.0, 260.0, 300.0 };
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,
0.841, 0.865, 0.890, 0.900, 0.910, 0.920, 0.930, 0.935, 0.940 };
EMNR::NP::NP(
int _incr,
double _rate,
int _msize,
std::vector<double>& _lambda_y,
std::vector<double>& _lambda_d
) :
incr(_incr),
rate(_rate),
msize(_msize),
lambda_y(_lambda_y),
lambda_d(_lambda_d)
{
{
double tau = -128.0 / 8000.0 / log(0.7);
alphaCsmooth = exp(-incr / rate / tau);
}
{
double tau = -128.0 / 8000.0 / log(0.96);
alphaMax = exp(-incr / rate / tau);
}
{
double tau = -128.0 / 8000.0 / log(0.7);
alphaCmin = exp(-incr / rate / tau);
}
{
double tau = -128.0 / 8000.0 / log(0.3);
alphaMin_max_value = exp(-incr / rate / tau);
}
snrq = -incr / (0.064 * rate);
double tau4 = -128.0 / 8000.0 / log(0.8);
betamax = exp(-incr / rate / tau4);
invQeqMax = 0.5;
av = 2.12;
Dtime = 8.0 * 12.0 * 128.0 / 8000.0;
U = 8;
V = (int)(0.5 + (Dtime * rate / (U * incr)));
if (V < 4)
V = 4;
if ((U = (int)(0.5 + (Dtime * rate / (V * incr)))) < 1)
U = 1;
D = U * V;
interpM(&MofD, D, 18, DVals, MVals);
interpM(&MofV, V, 18, DVals, MVals);
invQbar_points[0] = 0.03;
invQbar_points[1] = 0.05;
invQbar_points[2] = 0.06;
invQbar_points[3] = std::numeric_limits<double>::max();;
{
double db;
db = 10.0 * log10(8.0) / (12.0 * 128 / 8000);
nsmax[0] = pow(10.0, db / 10.0 * V * incr / rate);
db = 10.0 * log10(4.0) / (12.0 * 128 / 8000);
nsmax[1] = pow(10.0, db / 10.0 * V * incr / rate);
db = 10.0 * log10(2.0) / (12.0 * 128 / 8000);
nsmax[2] = pow(10.0, db / 10.0 * V * incr / rate);
db = 10.0 * log10(1.2) / (12.0 * 128 / 8000);
nsmax[3] = pow(10.0, db / 10.0 * V * incr / rate);
}
p.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
alphaOptHat.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
alphaHat.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
sigma2N.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
pbar.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
p2bar.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
Qeq.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
bmin.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
bmin_sub.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
k_mod.resize(msize); // (int *)malloc0(np.msize * sizeof(int));
actmin.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
actmin_sub.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
lmin_flag.resize(msize); // (int *)malloc0(np.msize * sizeof(int));
pmin_u.resize(msize); // (float *)malloc0(np.msize * sizeof(float));
actminbuff.resize(U); // (float**)malloc0(np.U * sizeof(float*));
for (int i = 0; i < U; i++) {
actminbuff[i].resize(msize); // (float *)malloc0(np.msize * sizeof(float));
}
{
int k, ku;
alphaC = 1.0;
subwc = V;
amb_idx = 0;
for (k = 0; k < msize; k++) {
lambda_y[k] = 0.5;
}
std::copy(lambda_y.begin(), lambda_y.end(), p.begin());
std::copy(lambda_y.begin(), lambda_y.end(), sigma2N.begin());
std::copy(lambda_y.begin(), lambda_y.end(), pbar.begin());
std::copy(lambda_y.begin(), lambda_y.end(), pmin_u.begin());
for (k = 0; k < msize; k++)
{
p2bar[k] = lambda_y[k] * lambda_y[k];
actmin[k] = std::numeric_limits<double>::max();
actmin_sub[k] = std::numeric_limits<double>::max();;
for (ku = 0; ku < U; ku++) {
actminbuff[ku][k] = std::numeric_limits<double>::max();;
}
}
std::fill(lmin_flag.begin(), lmin_flag.end(), 0);
}
}
void EMNR::NP::interpM (
double* res,
double x,
int nvals,
const std::array<double, 18>& xvals,
const std::array<double, 18>& yvals
)
{
if (x <= xvals[0])
{
*res = yvals[0];
}
else if (x >= xvals[nvals - 1])
{
*res = yvals[nvals - 1];
}
else
{
int idx = 1;
double xllow, xlhigh, frac;
while ((x >= xvals[idx]) && (idx < nvals - 1))
idx++;
xllow = log10 (xvals[idx - 1]);
xlhigh = log10(xvals[idx]);
frac = (log10 (x) - xllow) / (xlhigh - xllow);
*res = yvals[idx - 1] + frac * (yvals[idx] - yvals[idx - 1]);
}
}
void EMNR::NP::LambdaD()
{
int k;
double f0, f1, f2, f3;
double sum_prev_p;
double sum_lambda_y;
double alphaCtilda;
double sum_prev_sigma2N;
double alphaMin, SNR;
double beta, varHat, invQeq;
double invQbar;
double bc;
double QeqTilda, QeqTildaSub;
double noise_slope_max;
sum_prev_p = 0.0;
sum_lambda_y = 0.0;
sum_prev_sigma2N = 0.0;
for (k = 0; k < msize; k++)
{
sum_prev_p += p[k];
sum_lambda_y += lambda_y[k];
sum_prev_sigma2N += sigma2N[k];
}
for (k = 0; k < msize; k++)
{
f0 = p[k] / sigma2N[k] - 1.0;
alphaOptHat[k] = 1.0 / (1.0 + f0 * f0);
}
SNR = sum_prev_p / sum_prev_sigma2N;
alphaMin = std::min (alphaMin_max_value, pow (SNR, snrq));
for (k = 0; k < msize; k++)
if (alphaOptHat[k] < alphaMin) alphaOptHat[k] = alphaMin;
f1 = sum_prev_p / sum_lambda_y - 1.0;
alphaCtilda = 1.0 / (1.0 + f1 * f1);
alphaC = alphaCsmooth * alphaC + (1.0 - alphaCsmooth) * std::max (alphaCtilda, alphaCmin);
f2 = alphaMax * alphaC;
for (k = 0; k < msize; k++)
alphaHat[k] = f2 * alphaOptHat[k];
for (k = 0; k < msize; k++)
p[k] = alphaHat[k] * p[k] + (1.0 - alphaHat[k]) * lambda_y[k];
invQbar = 0.0;
for (k = 0; k < msize; k++)
{
beta = std::min (betamax, alphaHat[k] * alphaHat[k]);
pbar[k] = beta * pbar[k] + (1.0 - beta) * p[k];
p2bar[k] = beta * p2bar[k] + (1.0 - beta) * p[k] * p[k];
varHat = p2bar[k] - pbar[k] * pbar[k];
invQeq = varHat / (2.0 * sigma2N[k] * sigma2N[k]);
if (invQeq > invQeqMax)
invQeq = invQeqMax;
Qeq[k] = 1.0 / invQeq;
invQbar += invQeq;
}
invQbar /= (double) msize;
bc = 1.0 + av * sqrt (invQbar);
for (k = 0; k < msize; k++)
{
QeqTilda = (Qeq[k] - 2.0 * MofD) / (1.0 - MofD);
QeqTildaSub = (Qeq[k] - 2.0 * MofV) / (1.0 - MofV);
bmin[k] = 1.0 + 2.0 * (D - 1.0) / QeqTilda;
bmin_sub[k] = 1.0 + 2.0 * (V - 1.0) / QeqTildaSub;
}
std::fill(k_mod.begin(), k_mod.end(), 0);
for (k = 0; k < msize; k++)
{
f3 = p[k] * bmin[k] * bc;
if (f3 < actmin[k])
{
actmin[k] = f3;
actmin_sub[k] = p[k] * bmin_sub[k] * bc;
k_mod[k] = 1;
}
}
if (subwc == V)
{
if (invQbar < invQbar_points[0])
noise_slope_max = nsmax[0];
else if (invQbar < invQbar_points[1])
noise_slope_max = nsmax[1];
else if (invQbar < invQbar_points[2])
noise_slope_max = nsmax[2];
else
noise_slope_max = nsmax[3];
for (k = 0; k < msize; k++)
{
int ku;
double min;
if (k_mod[k])
lmin_flag[k] = 0;
actminbuff[amb_idx][k] = actmin[k];
min = std::numeric_limits<double>::max();;
for (ku = 0; ku < U; ku++)
{
if (actminbuff[ku][k] < min)
min = actminbuff[ku][k];
}
pmin_u[k] = min;
if ((lmin_flag[k] == 1)
&& (actmin_sub[k] < noise_slope_max * pmin_u[k])
&& (actmin_sub[k] > pmin_u[k]))
{
pmin_u[k] = actmin_sub[k];
for (ku = 0; ku < U; ku++)
actminbuff[ku][k] = actmin_sub[k];
}
lmin_flag[k] = 0;
actmin[k] = std::numeric_limits<double>::max();;
actmin_sub[k] = std::numeric_limits<double>::max();;
}
if (++amb_idx == U)
amb_idx = 0;
subwc = 1;
}
else
{
if (subwc > 1)
{
for (k = 0; k < msize; k++)
{
if (k_mod[k])
{
lmin_flag[k] = 1;
sigma2N[k] = std::min (actmin_sub[k], pmin_u[k]);
pmin_u[k] = sigma2N[k];
}
}
}
++subwc;
}
std::copy(sigma2N.begin(), sigma2N.end(), lambda_d.begin());
}
EMNR::G::G(
int _incr,
double _rate,
int _msize,
std::vector<double>& _mask,
const std::vector<float>& _y
) :
incr(_incr),
rate(_rate),
msize(_msize),
mask(_mask),
y(_y)
{
lambda_y.resize(msize); // (float *)malloc0(msize * sizeof(float));
lambda_d.resize(msize); // (float *)malloc0(msize * sizeof(float));
prev_gamma.resize(msize); // (float *)malloc0(msize * sizeof(float));
prev_mask.resize(msize); // (float *)malloc0(msize * sizeof(float));
gf1p5 = sqrt(PI) / 2.0;
{
double tau = -128.0 / 8000.0 / log(0.98);
alpha = exp(-incr / rate / tau);
}
eps_floor = std::numeric_limits<double>::min();
gamma_max = 1000.0;
q = 0.2;
std::fill(prev_mask.begin(), prev_mask.end(), 1.0);
std::fill(prev_gamma.begin(), prev_gamma.end(), 1.0);
gmax = 10000.0;
std::copy(Calculus::GG.begin(), Calculus::GG.end(), GG.begin());
std::copy(Calculus::GGS.begin(), Calculus::GGS.end(), GGS.begin());
// We keep this pretty useless part just in case...
if ((fileb = fopen("calculus", "rb")))
{
std::array<double, 241*241> gg;
std::size_t lgg = fread(&gg[0], sizeof(double), 241 * 241, fileb);
if (lgg != 241 * 241) {
fprintf(stderr, "GG file has an invalid size\n");
} else {
std::copy(gg.begin(), gg.end(), GG.begin());
}
std::array<double, 241*241> ggs;
std::size_t lggs =fread(&ggs[0], sizeof(double), 241 * 241, fileb);
if (lggs != 241 * 241) {
fprintf(stderr, "GGS file has an invalid size\n");
} else {
std::copy(ggs.begin(), ggs.end(), GGS.begin());
}
fclose(fileb);
}
}
void EMNR::G::calc_gamma0()
{
double gamma, eps_hat, v;
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);
v = (eps_hat / (1.0 + eps_hat)) * gamma;
mask[k] = gf1p5 * sqrt (v) / gamma * exp (- 0.5 * v)
* ((1.0 + v) * bessI0 (0.5 * v) + v * bessI1 (0.5 * v));
{
double v2 = std::min (v, 700.0);
double eta = mask[k] * mask[k] * lambda_y[k] / lambda_d[k];
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;
if (mask[k] != mask[k])
mask[k] = 0.01;
prev_gamma[k] = gamma;
prev_mask[k] = mask[k];
}
}
void EMNR::G::calc_gamma1()
{
double gamma, eps_hat, v, 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;
if (mask[k] != mask[k])
mask[k] = 0.01;
prev_gamma[k] = gamma;
prev_mask[k] = mask[k];
}
}
void EMNR::G::calc_gamma2()
{
double gamma, eps_hat, 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, 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, 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, ga, r, t, t0;
int k, 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, sum, inv_coherent_gain;
switch (wintype)
{
case 0:
arg = 2.0 * PI / (double) fsize;
sum = 0.0;
for (i = 0; i < fsize; i++)
{
window[i] = 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] *= inv_coherent_gain;
break;
}
}
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); // (float *)malloc0(fsize * sizeof(float));
inaccum.resize(iasize); // (float *)malloc0(iasize * sizeof(float));
forfftin.resize(fsize); // (float *)malloc0(fsize * sizeof(float));
forfftout.resize(msize * 2); // (float *)malloc0(msize * sizeof(complex));
mask.resize(msize); // (float *)malloc0(msize * sizeof(float));
std::fill(mask.begin(), mask.end(), 1.0);
revfftin.resize(msize * 2); // (float *)malloc0(msize * sizeof(complex));
revfftout.resize(fsize); // (float *)malloc0(fsize * sizeof(float));
save.resize(ovrlp); // (float **)malloc0(ovrlp * sizeof(float *));
for (int i = 0; i < ovrlp; i++)
save[i].resize(fsize); // (float *)malloc0(fsize * sizeof(float));
outaccum.resize(oasize); // (float *)malloc0(oasize * sizeof(float));
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()
{
int i;
std::fill(inaccum.begin(), inaccum.end(), 0);
for (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, m;
int N, n;
double sumPre, sumPost, zeta, 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 (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, ngamma2, nxi1 = 0, nxi2 = 0;
double tg, tx, dg, 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) {
ixi = ixi < 0 ? 0 : (ixi >= 241*241 ? 241*241 - 1 : ixi);
}
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;
}
switch (g->gain_method)
{
case 0:
g->calc_gamma0();
break;
case 1:
g->calc_gamma1();
break;
case 2:
g->calc_gamma2();
break;
}
if (g->ae_run)
aepf();
}
void EMNR::execute(int _pos)
{
if (run && _pos == position)
{
int i, j, k, sbuff, 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] = g1 * forfftout[2 * i + 0];
revfftin[2 * i + 1] = 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
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