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view toolboxes/FullBNT-1.0.7/bnt/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_matrix.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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function obslik = mk_hmm_obs_lik_matrix(engine, evidence) T = size(evidence,2); Q = length(engine.startprob); obslik = ones(Q, T); bnet = bnet_from_engine(engine); % P(o1,o2| Q1,Q2) = P(o1|Q1,Q2) * P(o2|Q1,Q2) onodes = bnet.observed; for i=1:length(onodes) data = cell2num(evidence(onodes(i),:)); if bnet.auto_regressive(onodes(i)) params = engine.obsprob{i}; mu = params.big_mu; Sigma = params.big_Sigma, W = params.big_W; mu0 = params.big_mu0; Sigma0 = params.big_Sigma0; %obslik_i = mk_arhmm_obs_lik(data, mu, Sigma, W, mu0, Sigma0 obslik_i = clg_prob(data(:,1:T-1), data(:,2:T), mu, Sigma, W); obslik_i = [mixgauss_prob(data(:,1), mu0, Sigma0) obslik_i]; elseif myismember(onodes(i), bnet.dnodes) %obslik_i = eval_pdf_cond_multinomial(data, engine.obsprob{i}.big_CPT); obslik_i = multinomial_prob(data, engine.obsprob{i}.big_CPT); else %obslik_i = eval_pdf_cond_gauss(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma); obslik_i = mixgauss_prob(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma); end obslik = obslik .* obslik_i; end