comparison toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/viterbi1.m @ 0:e9a9cd732c1e tip

first hg version after svn

+% Compute Viterbi path discrete HMM by different methods
+
+intra = zeros(2);
+intra(1,2) = 1;
+inter = zeros(2);
+inter(1,1) = 1;
+n = 2;
+
+Q = 2; % num hidden states
+O = 2; % num observable symbols
+
+ns = [Q O];
+dnodes = 1:2;
+onodes = [2];
+eclass1 = [1 2];
+eclass2 = [3 2];
+bnet = mk_dbn(intra, inter, ns, 'discrete', dnodes, 'eclass1', eclass1, 'eclass2', eclass2, ...
+	      'observed', onodes);
+
+for seed=1:10
+rand('state', seed);
+prior = normalise(rand(Q,1));
+transmat = mk_stochastic(rand(Q,Q));
+obsmat = mk_stochastic(rand(Q,O));
+bnet.CPD{1} = tabular_CPD(bnet, 1, prior);
+bnet.CPD{2} = tabular_CPD(bnet, 2, obsmat);
+bnet.CPD{3} = tabular_CPD(bnet, 3, transmat);
+
+
+% Create a sequence
+T = 5; 
+ev = sample_dbn(bnet, T);
+evidence = cell(2,T);
+evidence(2,:) = ev(2,:); % extract observed component
+data = cell2num(ev(2,:));
+
+%obslik = mk_dhmm_obs_lik(data, obsmat);
+obslik = multinomial_prob(data, obsmat);
+path = viterbi_path(prior, transmat, obslik);
+
+engine = {};
+engine{end+1} = smoother_engine(jtree_2TBN_inf_engine(bnet));
+
+mpe = find_mpe(engine{1}, evidence);
+
+assert(isequal(cell2num(mpe(1,:)), path)) % extract values of hidden nodes
+end