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1 % Script to reproduce the experiments leading to the results provided in the
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2 % Table 2 of the paper "Deep Scattering Spectrum" by J. Andén and S. Mallat.
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3
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4 % M=2 scattering, frequency scattering
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5
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6 preffix = 'time_freq_scat_l2_';
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7
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8 N = 5*2^17;
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9
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10 global src;
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11
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12 filt1_opt.filter_type = {'gabor_1d','morlet_1d'};
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13 filt1_opt.Q = [8 1];
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14 filt1_opt.J = T_to_J(8192*2,filt1_opt);
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15
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16 sc1_opt.M = 2;
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17
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18 ffilt1_opt.filter_type = 'morlet_1d';
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19 ffilt1_opt.J = 7;
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20
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21 fsc1_opt.M = 1;
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22
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23 Wop1 = wavelet_factory_1d(N, filt1_opt, sc1_opt);
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24 fWop1 = wavelet_factory_1d(128, ffilt1_opt, fsc1_opt);
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25
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26 scatt_fun1 = @(x)(log_scat(renorm_scat(scat(x,Wop1))));
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27 fscatt_fun1 = @(x)(func_output(@scat_freq,2,scatt_fun1(x),fWop1));
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28 feature_fun1 = @(x)(format_scat(fscatt_fun1(x)));
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29
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30 features = {feature_fun1};
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31
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32 for k = 1:length(features)
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33 fprintf('testing feature #%d...',k);
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34 tic;
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35 sz = size(features{k}(randn(N,1)));
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36 aa = toc;
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37 fprintf('OK (%.2fs) (size [%d,%d])\n',aa,sz(1),sz(2));
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38 end
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39
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40 db = prepare_database(src,features);
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41 db.features = single(db.features);
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42 db = svm_calc_kernel(db,'gaussian','square',1:8:size(db.features,2));
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43
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44 optt.kernel_type = 'gaussian';
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45 optt.C = 2.^[0:4:8];
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46 optt.gamma = 2.^[-16:4:-8];
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47 optt.search_depth = 3;
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48 optt.full_test_kernel = 1;
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49
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50 classify(db, optt, preffix);
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