function [outsig, fc] = lopezpoveda2001(insig,fs,varargin)
%lopezpoveda2001 Dual Resonance Nonlinear Filterbank
% Usage: outsig = lopezpoveda2001(insig,fs);
%
% LOPEZPOVEDA2001(insig,fs) computes the Dual Resonance Non-Linear (lopezpoveda2001)
% filterbank of the input signal insig sampled at fs Hz with channels
% specified by the center frequencies in fc. The lopezpoveda2001 is described in
% the paper Lopez-Poveda and Meddis (2001). The lopezpoveda2001 models the basilar
% membrane non-linearity.
%
% This version of the lopezpoveda2001 incoorperate the middle-ear filter used in
% Lopez-Poveda and Meddis (2001).
%
% The lopezpoveda2001 takes a lot of parameters which vary over frequency. Such a
% parameter is described by a 1 x2 vector [b a] and indicates
% that the value of the parameter at frequency fc can be calculated by
%
% 10^(b+a*log10(fc));
%
% The parameters are:
%
% 'flow',flow Set the lowest frequency in the filterbank to
% flow. Default value is 80 Hz.
%
% 'fhigh',fhigh Set the highest frequency in the filterbank to
% fhigh. Default value is 8000 Hz.
%
% 'basef',basef Ensure that the frequency basef is a centre frequency
% in the filterbank. The default value of [] means
% no default.
%
% 'middleear' Perform middleear filtering before the actual lopezpoveda2001
% is applied using the middleear filter specified in
% Lopez-Poveda and Meddis (2001), and compensate for
% the effect of the filter after lopezpoveda2001 filtering.
% This is the default.
%
% 'nomiddleear' No middle-ear filtering. Be carefull with this setting,
% as another scaling must then be perform to convert the
% input to stapes movement.
%
% 'bothparts' Compute both the linear and the non-linear path of
% the lopezpoveda2001. This is the default.
%
% 'linonly' Compute only the linear path.
%
% 'nlinonly' Compute only the non-linear path.
%
% 'lin_ngt',n Number of cascaded gammatone filter in the linear
% part, default value is 2.
%
% 'lin_nlp',n Number of cascaded lowpass filters in the linear
% part, default value is 4
%
% 'lin_gain',g Gain in the linear part, default value is [4.20405 ...
% .47909].
%
% 'lin_fc',fc Centre frequencies of the gammatone filters in the
% linear part. Default value is [-0.06762 1.01679].
%
% 'lin_bw',bw Bandwidth of the gammatone filters in the linear
% part. Default value is [.03728 .78563]
%
% 'lin_lp_cutoff',c
% Cutoff frequency of the lowpass filters in the
% linear part. Default value is [-0.06762 1.01679 ]
%
% 'nlin_ngt_before',n
% Number of cascaded gammatone filters in the
% non-linear part before the broken stick
% non-linearity. Default value is 3.
%
% 'nlin_ngt_after',n
% Number of cascaded gammatone filters in the
% non-linear part after the broken stick
% non-linearity. The default value of [] means to use the 'before'
% value.
%
% 'nlin_nlp',n Number of cascaded lowpass filters in the
% non-linear part. Default value is 3.
%
% 'nlin_fc_before',fc
% Center frequencies of the gammatone filters in the
% non-linear part before the broken stick
% non-linearity. Default value is [-0.05252 1.01650].
%
% 'nlin_fc_after',fc
% Center frequencies of the gammatone filters in the
% non-linear part after the broken stick
% non-linearity. The default value of [] means to use the 'before'
% value.
%
% 'nlin_bw_before',bw
% Bandwidth of the gammatone filters in the
% non-linear part before the broken stick
% non-linearity. Default value is [-0.03193 .77426 ].
%
% 'nlin_bw_after',w
% Bandwidth of the gammatone filters in the non-linear
% part after the broken stick non-linearity. The default
% value of [] means to use the 'before' value.
%
% 'nlin_lp_cutoff',c
% Cutoff frequency of the lowpass filters in the
% non-linear part. Default value is [-0.05252 1.01650 ].
%
% 'nlin_a',a The a coefficient for the broken-stick non-linearity. Default
% value is [1.40298 .81916 ].
%
% 'nlin_b',b The b coefficient for the broken-stick non-linearity. Default
% value is [1.61912 -.81867].
%
% 'nlin_c',c The c coefficient for the broken-stick non-linearity. Default
% value is [-.60206 0].
%
% 'nlin_d',d The d coefficient for the broken-stick non-linearity. Default
% value is 1.
%
% The output from lopezpoveda2001 can be conveniently visualized using the
% plotfilterbank function from LTFAT.
%
% See also: middleearfilter
%
% References:
% E. Lopez-Poveda and R. Meddis. A human nonlinear cochlear filterbank.
% J. Acoust. Soc. Am., 110:3107--3118, 2001.
%
% R. Meddis, L. O'Mard, and E. Lopez-Poveda. A computational algorithm
% for computing nonlinear auditory frequency selectivity. J. Acoust. Soc.
% Am., 109:2852--2861, 2001.
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.10.0/doc/models/lopezpoveda2001.php
% Copyright (C) 2009-2020 Piotr Majdak and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 0.10.0
%
% 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 3 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, see <http://www.gnu.org/licenses/>.
% AUTHOR: Morten Løve Jepsen
% Bugfixes by Marton Marschall 9/2008 and Katarina Egger 2011
% Cleanup by Peter L. Søndergaard.
%
% In comparison to the original code, the gammatone filters are computed
% by convolving the filter coefficients, instead of performing multiple
% runs of 'filter'. The lowpass filtering is still performed by mutliple
% runs through 'filter', as the linear-part lowpass filter turned out to
% be unstable when the coefficients was convolved.
if nargin<2
error('%s: Too few input parameters.',upper(mfilename));
end;
% Import the parameters from the arg_drnl.m function.
definput.import={'lopezpoveda2001'};
[flags,kv]=ltfatarghelper({'flow','fhigh'},definput,varargin);
% Expand the 'after' settings, if they are empty.
if isempty(kv.nlin_ngt_after)
kv.nlin_ngt_after=kv.nlin_ngt_before;
end;
if isempty(kv.nlin_fc_after)
kv.nlin_fc_after=kv.nlin_fc_before;
end;
if isempty(kv.nlin_bw_after)
kv.nlin_bw_after=kv.nlin_bw_before;
end;
% find the center frequencies used in the filterbank, 1 ERB spacing
fc = erbspacebw(kv.flow, kv.fhigh, kv.bwmul, kv.basef);
%% Convert the input to column vectors
nchannels = length(fc);
% Change f to correct shape.
[insig,siglen,nsigs,wasrow,remembershape]=comp_sigreshape_pre(insig,'lopezpoveda2001',0);
outsig=zeros(siglen,nchannels,nsigs);
% The current implementation of the lopezpoveda2001 works with
% dboffset=100, so we must change to this setting.
% The output is always the same, so there is no need for changing back.
% Obtain the dboffset currently used.
dboffset=dbspl(1);
% Switch signal to the correct scaling.
insig=gaindb(insig,dboffset-100);
%% Apply the middle-ear filter
if flags.do_middleear
me_fir = middleearfilter(fs);
insig = filter(me_fir,1,insig);
end;
if flags.do_jepsenmiddleear
me_fir = middleearfilter(fs,'jepsenmiddleear');
insig = filter(me_fir,1,insig);
end;
%% ---------------- main loop over center frequencies
% Handle the compression limiting in the broken-stick non-linearity
if ~isempty(kv.compresslimit)
fclimit=min(fc,kv.compresslimit);
else
fclimit=fc;
end;
% Sanity checking, some center frequencies may go above the Nyquest
% frequency
% Happens for lin_lp_cutoff
for ii=1:nchannels
% -------- Setup channel dependant definitions -----------------
lin_fc = polfun(kv.lin_fc,fc(ii));
lin_bw = polfun(kv.lin_bw,fc(ii));
lin_lp_cutoff = polfun(kv.lin_lp_cutoff,fc(ii));
lin_gain = polfun(kv.lin_gain,fc(ii));
nlin_fc_before = polfun(kv.nlin_fc_before,fc(ii));
nlin_fc_after = polfun(kv.nlin_fc_after,fc(ii));
nlin_bw_before = polfun(kv.nlin_bw_before,fc(ii));
nlin_bw_after = polfun(kv.nlin_bw_after,fc(ii));
nlin_lp_cutoff = polfun(kv.nlin_lp_cutoff,fc(ii));
% Expand a and b using the (possibly) limited fc
nlin_a = polfun(kv.nlin_a,fclimit(ii));
% b [(m/s)^(1-c)]
nlin_b = polfun(kv.nlin_b,fclimit(ii));
nlin_c = polfun(kv.nlin_c,fc(ii));
% Compute gammatone coefficients for the linear stage
[GTlin_b,GTlin_a] = gammatone(lin_fc,fs,kv.lin_ngt,lin_bw/audfiltbw(lin_fc),'classic');
% Compute coefficients for the linear stage lowpass, use 2nd order
% Butterworth.
[LPlin_b,LPlin_a] = butter(2,lin_lp_cutoff/(fs/2));
% Compute gammatone coefficients for the non-linear stage
%[GTnlin_b_before,GTnlin_a_before] = coefGtDRNL(nlin_fc_before,nlin_bw_before,...
% kv.nlin_ngt_before,fs);
[GTnlin_b_before,GTnlin_a_before] = gammatone(nlin_fc_before,fs,kv.nlin_ngt_before,...
nlin_bw_before/audfiltbw(nlin_fc_before),'classic');
[GTnlin_b_after,GTnlin_a_after] = gammatone(nlin_fc_after,fs,kv.nlin_ngt_after,...
nlin_bw_after/audfiltbw(nlin_fc_after),'classic');
% Compute coefficients for the non-linear stage lowpass, use 2nd order
% Butterworth.
[LPnlin_b,LPnlin_a] = butter(2,nlin_lp_cutoff/(fs/2));
% -------------- linear part --------------------------------
if flags.do_bothparts || flags.do_linonly
% Apply linear gain
y_lin = insig.*lin_gain;
% Gammatone filtering
y_lin = filter(GTlin_b,GTlin_a,y_lin);
% Multiple LP filtering
for jj=1:kv.lin_nlp
y_lin = filter(LPlin_b,LPlin_a,y_lin);
end;
else
y_lin = zeros(size(insig));
end;
% -------------- Non-linear part ------------------------------
if flags.do_bothparts || flags.do_nlinonly
% GT filtering before
y_nlin = filter(GTnlin_b_before,GTnlin_a_before,insig);
% Broken stick nonlinearity
if kv.nlin_d~=1
% Just to save some flops, make this optional.
y_nlin = sign(y_nlin).*min(nlin_a*abs(y_nlin).^kv.nlin_d, ...
nlin_b*(abs(y_nlin)).^nlin_c);
else
y_nlin = sign(y_nlin).*min(nlin_a*abs(y_nlin), ...
nlin_b*(abs(y_nlin)).^nlin_c);
end;
% GT filtering after
y_nlin = filter(GTnlin_b_after,GTnlin_a_after,y_nlin);
% then LP filtering
for jj=1:kv.nlin_nlp
y_nlin = filter(LPnlin_b,LPnlin_a,y_nlin);
end;
else
y_nlin = zeros(size(insig));
end;
outsig(:,ii,:) = reshape(y_lin + y_nlin,siglen,1,nsigs);
end;
function outpar=polfun(par,fc)
%outpar=10^(par(1)+par(2)*log10(fc));
outpar=10^(par(1))*fc^par(2);