comparison toolboxes/FullBNT-1.0.7/HMM/mhmm_em_demo.m @ 0:e9a9cd732c1e tip

first hg version after svn

+if 1
+  O = 4;
+  T = 10;
+  nex = 50;
+  M = 2;
+  Q = 3;
+else
+  O = 8;          %Number of coefficients in a vector 
+  T = 420;         %Number of vectors in a sequence 
+  nex = 1;        %Number of sequences 
+  M = 1;          %Number of mixtures 
+  Q = 6;          %Number of states 
+end
+cov_type = 'full';
+
+data = randn(O,T,nex);
+
+% initial guess of parameters
+prior0 = normalise(rand(Q,1));
+transmat0 = mk_stochastic(rand(Q,Q));
+
+if 0
+  Sigma0 = repmat(eye(O), [1 1 Q M]);
+  % Initialize each mean to a random data point
+  indices = randperm(T*nex);
+  mu0 = reshape(data(:,indices(1:(Q*M))), [O Q M]);
+  mixmat0 = mk_stochastic(rand(Q,M));
+else
+  [mu0, Sigma0] = mixgauss_init(Q*M, data, cov_type);
+  mu0 = reshape(mu0, [O Q M]);
+  Sigma0 = reshape(Sigma0, [O O Q M]);
+  mixmat0 = mk_stochastic(rand(Q,M));
+end
+
+[LL, prior1, transmat1, mu1, Sigma1, mixmat1] = ...
+    mhmm_em(data, prior0, transmat0, mu0, Sigma0, mixmat0, 'max_iter', 5);
+
+
+loglik = mhmm_logprob(data, prior1, transmat1, mu1, Sigma1, mixmat1);
+