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

user: boblsturm
branch 'default'
added README.md
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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
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/matlab/nmf_beta.m	Sun Jun 18 06:26:13 2017 -0400
@@ -0,0 +1,35 @@
+function [ Y, cost ] = nmf_beta( V, W, varargin )
+
+if nargin > 2
+    nmf_params = varargin{1};
+    iterations = nmf_params.Iterations;
+    lambda = nmf_params.Lambda;
+    beta = nmf_params.Beta % 1: KL Divergence; 2: Euclidean
+end
+
+cost=0;
+K=size(W, 2);
+M=size(V, 2);
+
+H=random('unif',0, 1, K, M);
+
+V = V+1E-6;
+W = W+1E-6;
+
+for l=1:L-1    
+    recon = W*H;
+    num = H.*(W'*(((recon).^(beta-2)).*V));
+    den = W'*((recon).^(beta-1));
+    H = num./den;    
+end
+
+fprintf('Iterations: %i/%i\n', l, L);
+fprintf('Convergence Criteria: %i\n', convergence*100);
+fprintf('Repitition: %i\n', r);
+fprintf('Polyphony: %i\n', p);
+fprintf('Continuity: %i\n', c);
+
+Y=H;
+Y = Y./max(max(Y)); %Normalize activations
+
+end