comparison src/matlab/nmf_beta.m @ 0:c52bc3e8d3ad tip

user: boblsturm branch 'default' added README.md added assets/.DS_Store added assets/playButton.jpg added assets/stopButton.png added assets/swapButton.jpg added data/.DS_Store added data/fiveoctaves.mp3 added data/glock2.wav added data/sinScale.mp3 added data/speech_female.mp3 added data/sweep.wav added nimfks.m.lnk added src/.DS_Store added src/matlab/.DS_Store added src/matlab/AnalysisCache.m added src/matlab/CSS.m added src/matlab/DataHash.m added src/matlab/ExistsInCache.m added src/matlab/KLDivCost.m added src/matlab/LoadFromCache.m added src/matlab/SA_B_NMF.m added src/matlab/SaveInCache.m added src/matlab/Sound.m added src/matlab/SynthesisCache.m added src/matlab/chromagram_E.m added src/matlab/chromagram_IF.m added src/matlab/chromagram_P.m added src/matlab/chromsynth.m added src/matlab/computeSTFTFeat.m added src/matlab/controller.m added src/matlab/decibelSliderReleaseCallback.m added src/matlab/drawClickCallBack.m added src/matlab/fft2chromamx.m added src/matlab/hz2octs.m added src/matlab/ifgram.m added src/matlab/ifptrack.m added src/matlab/istft.m added src/matlab/nimfks.fig added src/matlab/nimfks.m added src/matlab/nmfFn.m added src/matlab/nmf_beta.m added src/matlab/nmf_divergence.m added src/matlab/nmf_euclidean.m added src/matlab/prune_corpus.m added src/matlab/rot_kernel.m added src/matlab/templateAdditionResynth.m added src/matlab/templateDelCb.m added src/matlab/templateScrollCb.m
author boblsturm
date Sun, 18 Jun 2017 06:26:13 -0400
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-1:000000000000 0:c52bc3e8d3ad
1 function [ Y, cost ] = nmf_beta( V, W, varargin )
2
3 if nargin > 2
4 nmf_params = varargin{1};
5 iterations = nmf_params.Iterations;
6 lambda = nmf_params.Lambda;
7 beta = nmf_params.Beta % 1: KL Divergence; 2: Euclidean
8 end
9
10 cost=0;
11 K=size(W, 2);
12 M=size(V, 2);
13
14 H=random('unif',0, 1, K, M);
15
16 V = V+1E-6;
17 W = W+1E-6;
18
19 for l=1:L-1
20 recon = W*H;
21 num = H.*(W'*(((recon).^(beta-2)).*V));
22 den = W'*((recon).^(beta-1));
23 H = num./den;
24 end
25
26 fprintf('Iterations: %i/%i\n', l, L);
27 fprintf('Convergence Criteria: %i\n', convergence*100);
28 fprintf('Repitition: %i\n', r);
29 fprintf('Polyphony: %i\n', p);
30 fprintf('Continuity: %i\n', c);
31
32 Y=H;
33 Y = Y./max(max(Y)); %Normalize activations
34
35 end