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1 % Copyright 2012, Google, Inc.
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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 fig_offset2 = 30;
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33 fig_offset3 = 50;
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34
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35 if nargin < 2
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36 n_scales = 20;
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37 end
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38
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39 smoothed = waves;
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40
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41 for scale_no = 1:n_scales
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42
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43 if mod(scale_no, 2) == 1
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44 newsmoothed = filter([1, 1]/2, 1, smoothed);
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45 diffsmoothed = max(0, smoothed - newsmoothed);
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46 smoothed = newsmoothed;
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47 else
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48 newsmoothed = filter([1, 2, 1]/4, 1, smoothed);
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49 diffsmoothed = max(0, smoothed - newsmoothed);
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50 smoothed = newsmoothed(1:2:end, :);
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51 end
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52
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53 figure(scale_no + fig_offset1)
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54 imagesc(squeeze(smoothed(:,:,1))')
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55
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56 figure(scale_no + fig_offset2)
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57 plot(squeeze(mean(smoothed, 2)));
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58
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59 drawnow
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60 pause(1)
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61
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62 end
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63
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64
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65 function waves = deskew(waves)
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66
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67 for col = 1:size(waves, 2)
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68 waves(1:(end-col+1), col) = waves(col:end, col);
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69 end
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70
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