tom@455: % Copyright 2012, Google, Inc.
dicklyon@462: % Author Richard F. Lyon
tom@455: %
tom@455: % This Matlab file is part of an implementation of Lyon's cochlear model:
tom@455: % "Cascade of Asymmetric Resonators with Fast-Acting Compression"
tom@455: % to supplement Lyon's upcoming book "Human and Machine Hearing"
tom@455: %
tom@455: % Licensed under the Apache License, Version 2.0 (the "License");
tom@455: % you may not use this file except in compliance with the License.
tom@455: % You may obtain a copy of the License at
tom@455: %
tom@455: %     http://www.apache.org/licenses/LICENSE-2.0
tom@455: %
tom@455: % Unless required by applicable law or agreed to in writing, software
tom@455: % distributed under the License is distributed on an "AS IS" BASIS,
tom@455: % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
tom@455: % See the License for the specific language governing permissions and
tom@455: % limitations under the License.
tom@455: 
dicklyon@473: function [CF, decim_naps, naps] = CARFAC_Run ...
tom@455:   (CF, input_waves, AGC_plot_fig_num)
dicklyon@473: % function [CF, decim_naps, naps] = CARFAC_Run ...
dicklyon@462: %   (CF, input_waves, AGC_plot_fig_num)
tom@455: % This function runs the CARFAC; that is, filters a 1 or more channel
tom@455: % sound input to make one or more neural activity patterns (naps).
tom@455: %
tom@455: % The CF struct holds the filterbank design and state; if you want to
tom@455: % break the input up into segments, you need to use the updated CF
tom@455: % to keep the state between segments.
tom@455: %
tom@455: % input_waves is a column vector if there's just one audio channel;
tom@455: % more generally, it has a row per time sample, a column per audio channel.
tom@455: %
tom@455: % naps has a row per time sample, a column per filterbank channel, and
tom@455: % a layer per audio channel if more than 1.
tom@455: % decim_naps is like naps but time-decimated by the int CF.decimation.
tom@455: %
tom@455: % the input_waves are assumed to be sampled at the same rate as the
tom@455: % CARFAC is designed for; a resampling may be needed before calling this.
tom@455: %
tom@455: % The function works as an outer iteration on time, updating all the
tom@455: % filters and AGC states concurrently, so that the different channels can
tom@455: % interact easily.  The inner loops are over filterbank channels, and
tom@455: % this level should be kept efficient.
tom@455: 
dicklyon@473: [n_samp, n_ears] = size(input_waves);
tom@455: n_ch = CF.n_ch;
tom@455: 
tom@455: if nargin < 3
tom@455:   AGC_plot_fig_num = 0;
tom@455: end
tom@455: 
dicklyon@473: if n_ears ~= CF.n_ears
tom@455:   error('bad number of input_waves channels passed to CARFAC_Run')
tom@455: end
tom@455: 
dicklyon@473: 
dicklyon@473: naps = zeros(n_samp, n_ch, n_ears);
dicklyon@473: 
dicklyon@473: seglen = 16;
dicklyon@473: n_segs = ceil(n_samp / seglen);
dicklyon@473: 
dicklyon@473: if nargout > 1
tom@455:   % make decimated detect output:
dicklyon@473:   decim_naps = zeros(n_segs, CF.n_ch, CF.n_ears);
tom@455: else
tom@455:   decim_naps = [];
tom@455: end
tom@455: 
dicklyon@473: if nargout > 2
dicklyon@473:   % make decimated detect output:
dicklyon@473:   naps = zeros(n_samp, CF.n_ch, CF.n_ears);
dicklyon@473: else
dicklyon@473:   naps = [];
dicklyon@473: end
tom@455: 
dicklyon@473: for seg_num = 1:n_segs
dicklyon@473:   if seg_num == n_segs
dicklyon@473:     % The last segement may be short of seglen, but do it anyway:
dicklyon@473:     k_range = (seglen*(seg_num - 1) + 1):n_samp;
dicklyon@473:   else
dicklyon@473:     k_range = seglen*(seg_num - 1) + (1:seglen);
tom@455:   end
dicklyon@473:   % Process a segment to get a slice of decim_naps, and plot AGC state:
dicklyon@473:   [seg_naps, CF] = CARFAC_Run_Segment(CF, input_waves(k_range, :));
dicklyon@473:   
dicklyon@473:   if ~isempty(naps)
dicklyon@473:     for ear = 1:n_ears
dicklyon@473:       % Accumulate segment naps to make full naps
dicklyon@473:       naps(k_range, :, ear) = seg_naps(:, :, ear);
tom@455:     end
dicklyon@462:   end
dicklyon@462:   
dicklyon@473:   if ~isempty(decim_naps)
dicklyon@473:     for ear = 1:n_ears
dicklyon@473:       decim_naps(seg_num, :, ear) = CF.IHC_state(ear).ihc_accum / seglen;
dicklyon@473:       CF.IHC_state(ear).ihc_accum = zeros(n_ch,1);
dicklyon@473:     end
tom@455:   end
dicklyon@462:   
dicklyon@473:   if AGC_plot_fig_num
dicklyon@462:     figure(AGC_plot_fig_num); hold off; clf
dicklyon@462:     set(gca, 'Position', [.25, .25, .5, .5])
dicklyon@462:     
dicklyon@473:     for ear = 1:n_ears
dicklyon@473:       plot(CF.AGC_state(ear).AGC_memory(:, 1), 'k-', 'LineWidth', 1)
dicklyon@473:       maxes(ear) = max(CF.AGC_state(ear).AGC_memory(:));
dicklyon@462:       hold on
dicklyon@462:       for stage = 1:3;
dicklyon@473:         plot(2^(stage-1) * (CF.AGC_state(ear).AGC_memory(:, stage) - ...
dicklyon@473:           2 * CF.AGC_state(ear).AGC_memory(:, stage+1)));
dicklyon@462:       end
dicklyon@462:       stage = 4;
dicklyon@473:       plot(2^(stage-1) * CF.AGC_state(ear).AGC_memory(:, stage));
dicklyon@462:     end
dicklyon@473:     axis([0, CF.n_ch+1, 0.0, max(maxes) + 0.01]);
dicklyon@462:     drawnow
dicklyon@462:   end
dicklyon@473: 
tom@455: end
tom@455: 
dicklyon@473: 
dicklyon@473: