Mercurial > hg > aimc
view trunk/matlab/bmm/carfac/CARFAC_hacking.m @ 563:fb602edc2d55
Separate the OHC nonlinear function into new file CARFAC_OHC_NLF.m. Update Design doc a bit. Add optional outputs and hacks that I used with Roy to look at distortion effects in OHC.
author | dicklyon@google.com |
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date | Sat, 12 May 2012 04:31:59 +0000 |
parents | 3dff17554c6d |
children | 3e2e0ab4f708 |
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% Copyright 2012, Google, Inc. % Author: Richard F. Lyon % % This Matlab file is part of an implementation of Lyon's cochlear model: % "Cascade of Asymmetric Resonators with Fast-Acting Compression" % to supplement Lyon's upcoming book "Human and Machine Hearing" % % Licensed under the Apache License, Version 2.0 (the "License"); % you may not use this file except in compliance with the License. % You may obtain a copy of the License at % % http://www.apache.org/licenses/LICENSE-2.0 % % Unless required by applicable law or agreed to in writing, software % distributed under the License is distributed on an "AS IS" BASIS, % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. % See the License for the specific language governing permissions and % limitations under the License. %% Test/demo hacking for CARFAC Matlab stuff: clear variables %% use_plan_file = 1; if use_plan_file file_signal = wavread('plan.wav'); % file_signal = file_signal(8100+(1:20000)); % trim for a faster test file_signal = file_signal(10000+(1:10000)); % trim for a faster test else flist = [1000]; alist = [1]; flist = 1000; alist = 1; sine_signal = 0; times = (0:19999)' / 22050; for fno = 1:length(flist) sine_signal = sine_signal + alist(fno)*sin(flist(fno)*2*pi*times); end growth_power = 0; % use 0 for flat, 4 or more for near exponential file_signal = 1.0 * (sine_signal .* (times/max(times)).^growth_power); end % repeat with negated signal to compare responses: % file_signal = [file_signal; -file_signal]; % make a long test signal by repeating at different levels: do_distortion_figs = 0; % use 1 for distortion figure hack.... if do_distortion_figs dB_list = -40:20:0 else dB_list = -80:20:60 end % dB = dB_list(1); % test_signal = 10^(dB/20)* file_signal(1:4000) % lead-in []; test_signal = []; for dB = dB_list test_signal = [test_signal; file_signal * 10^(dB/20)]; end %% Run mono, then stereo test: agc_plot_fig_num = 6; for n_ears = 1 % 1:2 CF_struct = CARFAC_Design(n_ears); % default design if n_ears == 2 % For the 2-channel pass, add a silent second channel: test_signal = [test_signal, zeros(size(test_signal))]; end CF_struct = CARFAC_Init(CF_struct); [CF_struct, nap_decim, nap, BM, ohc, agc] = CARFAC_Run(CF_struct, test_signal, ... agc_plot_fig_num); % nap = deskew(nap); % deskew doesn't make much difference % dB_BM = 10/log(10) * log(filter(1, [1, -0.995], BM(:, 20:50, :).^2)); dB_BM = 10/log(10) * log(filter(1, [1, -0.995], BM(:, :, :).^2)); % only ear 1: MultiScaleSmooth(dB_BM(5000:200:end, :, 1), 1); % Display results for 1 or 2 ears: for ear = 1:n_ears smooth_nap = nap_decim(:, :, ear); if n_ears == 1 mono_max = max(smooth_nap(:)); end figure(3 + ear + n_ears) % Makes figures 5, ... image(63 * ((max(0, smooth_nap)/mono_max)' .^ 0.5)) title('smooth nap from nap decim') colormap(1 - gray); end % Show resulting data, even though M-Lint complains: CF_struct CF_struct.ears(1).CAR_state CF_struct.ears(1).AGC_state min_max_decim = [min(nap_decim(:)), max(nap_decim(:))] %% if do_distortion_figs channels = [38, 39, 40]; times = 0000 + (3200:3599); smoothed_ohc = ohc; epsi = 0.4; % smoothed_ohc = filter(epsi, [1, -(1-epsi)], smoothed_ohc); % smoothed_ohc = filter(epsi, [1, -(1-epsi)], smoothed_ohc); figure(101); hold off plot(smoothed_ohc(times, channels)) hold on plot(smoothed_ohc(times, channels(2)), 'k-', 'LineWidth', 1.5) title('OHC') figure(105); hold off plot(agc(times, channels)) hold on plot(agc(times, channels(2)), 'k-', 'LineWidth', 1.5) title('AGC') figure(103); hold off plot(BM(times, channels)) hold on plot(BM(times, channels(2)), 'k-', 'LineWidth', 1.5) title('BM') extra_damping = smoothed_ohc + agc; figure(102); hold off plot(extra_damping(times, channels)) hold on plot(extra_damping(times, channels(2)), 'k-', 'LineWidth', 1.5) title('extra damping') distortion = -(extra_damping - smooth1d(extra_damping, 10)) .* BM; distortion = filter(epsi, [1, -(1-epsi)], distortion); distortion = filter(epsi, [1, -(1-epsi)], distortion); % distortion = filter(epsi, [1, -(1-epsi)], distortion); figure(104); hold off plot(distortion(times, channels)) hold on plot(distortion(times, channels(2)), 'k-', 'LineWidth', 1.5) title('distortion') end %% end % Expected result: Figure 3 looks like figure 2, a tiny bit darker. % and figure 4 is empty (all zero)