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1 % Copyright 2012 Google Inc. All Rights Reserved.
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2 % Author: Richard F. Lyon
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3 %
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4 % This Matlab file is part of an implementation of Lyon's cochlear model:
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5 % "Cascade of Asymmetric Resonators with Fast-Acting Compression"
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6 % to supplement Lyon's upcoming book "Human and Machine Hearing"
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7 %
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8 % Licensed under the Apache License, Version 2.0 (the "License");
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9 % you may not use this file except in compliance with the License.
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10 % You may obtain a copy of the License at
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11 %
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12 % http://www.apache.org/licenses/LICENSE-2.0
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13 %
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14 % Unless required by applicable law or agreed to in writing, software
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15 % distributed under the License is distributed on an "AS IS" BASIS,
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16 % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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17 % See the License for the specific language governing permissions and
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18 % limitations under the License.
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19
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20 function MultiScaleSmooth(waves, n_scales)
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21 % function MultiScaleSmooth(waves, n_scales)
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22 %
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23 % Let's take columns as waveforms, and smooth them to different scales;
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24 % these inputs can be carfac NAPs, for example, and the peaks of the
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25 % smoothed versions can be used as trigger events, even tracking back
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26 % to less-smoothed versions.
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27 % And we'll deciamte 2:1 at every other smoothing.
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28 %
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29 % Until we decide what we want, we'll just plot things, one plot per scale.
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30
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31 fig_offset1 = 10;
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32
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33 if nargin < 2
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34 n_scales = 20;
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35 end
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36
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37 smoothed = waves;
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38
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39 for scale_no = 1:n_scales
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40
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41 if mod(scale_no, 2) == 1
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42 newsmoothed = filter([1, 1]/2, 1, smoothed);
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43 diffsmoothed = max(0, smoothed - newsmoothed);
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44 smoothed = newsmoothed;
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45 else
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46 newsmoothed = filter([1, 2, 1]/4, 1, smoothed);
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47 diffsmoothed = max(0, smoothed - newsmoothed);
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48 smoothed = newsmoothed(1:2:end, :);
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49 end
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50
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51 figure(scale_no + fig_offset1)
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52 imagesc(squeeze(smoothed(:,:,1))')
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53
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54 drawnow
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55 pause(1)
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56
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57 end
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58
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