comparison toolboxes/FullBNT-1.0.7/docs/dbn_hmm_demo.m @ 0:e9a9cd732c1e tip

first hg version after svn

+ Example due to Wang Hee Lin" <[e-mail]
+
+
+intra = zeros(2);
+intra(1,2) = 1; 
+inter = zeros(2);
+inter(1,1) = 1; 
+
+Q = 2; % num hidden states
+O = 2; % num observable symbols
+ns = [Q O];%number of states
+dnodes = 1:2;
+%onodes = [1:2]; % only possible with jtree, not hmm
+onodes = [2]; 
+bnet = mk_dbn(intra, inter, ns, 'discrete', dnodes, 'observed', onodes);
+for i=1:4
+  bnet.CPD{i} = tabular_CPD(bnet, i);
+end
+
+prior0 = normalise(rand(Q,1));
+transmat0 = mk_stochastic(rand(Q,Q));
+obsmat0 = mk_stochastic(rand(Q,O));
+
+%engine = smoother_engine(hmm_2TBN_inf_engine(bnet));
+engine = smoother_engine(jtree_2TBN_inf_engine(bnet));
+
+ss = 2;%slice size(ss)
+ncases = 10;%number of examples
+T=10;
+max_iter=2;%iterations for EM
+cases = cell(1, ncases);
+for i=1:ncases
+  ev = sample_dbn(bnet, T);
+  cases{i} = cell(ss,T);
+  cases{i}(onodes,:) = ev(onodes, :);
+end
+[bnet2, LLtrace] = learn_params_dbn_em(engine, cases, 'max_iter', 4);