tom@516: % Copyright 2012, Google, Inc.
tom@516: % Author: Richard F. Lyon
tom@516: %
tom@516: % This Matlab file is part of an implementation of Lyon's cochlear model:
tom@516: % "Cascade of Asymmetric Resonators with Fast-Acting Compression"
tom@516: % to supplement Lyon's upcoming book "Human and Machine Hearing"
tom@516: %
tom@516: % Licensed under the Apache License, Version 2.0 (the "License");
tom@516: % you may not use this file except in compliance with the License.
tom@516: % You may obtain a copy of the License at
tom@516: %
tom@516: %     http://www.apache.org/licenses/LICENSE-2.0
tom@516: %
tom@516: % Unless required by applicable law or agreed to in writing, software
tom@516: % distributed under the License is distributed on an "AS IS" BASIS,
tom@516: % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
tom@516: % See the License for the specific language governing permissions and
tom@516: % limitations under the License.
tom@516: 
tom@516: function MultiScaleSmooth(waves, n_scales)
tom@516: % function MultiScaleSmooth(waves, n_scales)
tom@516: %
tom@516: % Let's take columns as waveforms, and smooth them to different scales;
tom@516: % these inputs can be carfac NAPs, for example, and the peaks of the
tom@516: % smoothed versions can be used as trigger events, even tracking back
tom@516: % to less-smoothed versions.
tom@516: % And we'll deciamte 2:1 at every other smoothing.
tom@516: %
tom@516: % Until we decide what we want, we'll just plot things, one plot per scale.
tom@516: 
tom@516: fig_offset1 = 10;
tom@516: fig_offset2 = 30;
tom@516: fig_offset3 = 50;
tom@516: 
tom@516: if nargin < 2
tom@516:   n_scales = 20;
tom@516: end
tom@516: 
tom@516: smoothed = waves;
tom@516: 
tom@516: for scale_no = 1:n_scales
tom@516: 
tom@516:   if mod(scale_no, 2) == 1
tom@516:     newsmoothed = filter([1, 1]/2, 1, smoothed);
tom@516:     diffsmoothed = max(0, smoothed - newsmoothed);
tom@516:     smoothed = newsmoothed;
tom@516:   else
tom@516:     newsmoothed = filter([1, 2, 1]/4, 1, smoothed);
tom@516:     diffsmoothed = max(0, smoothed - newsmoothed);
tom@516:     smoothed = newsmoothed(1:2:end, :);
tom@516:   end
tom@516: 
tom@516:   figure(scale_no + fig_offset1)
dicklyon@523:   imagesc(squeeze(smoothed(:,:,1))')
tom@516: 
tom@516:   figure(scale_no + fig_offset2)
dicklyon@523:   plot(squeeze(mean(smoothed, 2)));
tom@516: 
tom@516:   drawnow
tom@516:   pause(1)
tom@516: 
tom@516: end
tom@516: 
tom@516: 
tom@516: function waves = deskew(waves)
tom@516: 
tom@516: for col = 1:size(waves, 2)
tom@516:   waves(1:(end-col+1), col) = waves(col:end, col);
tom@516: end
tom@516: