mk_hmm_obs_lik_vec.m

Bayesian网络工具箱.

function obslik = mk_hmm_obs_lik_vec(engine, evidence)

Q = length(engine.startprob);
obslik = ones(Q, 1);
% P(o1,o2| Q1,Q2) = P(o1|Q1,Q2) * P(o2|Q1,Q2)
bnet = bnet_from_engine(engine);
onodes = bnet.observed;
for i=1:length(onodes)
  data = cell2num(evidence(onodes(i),1));
  if myismember(onodes(i), bnet.dnodes)
    obslik_i = mk_dhmm_obs_lik(data, engine.obsprob{i});
  else
    % calling mk_ghmm_obs_lik, which calls gaussian_prob, is slow, so we inline it
    % and use the pre-computed  inverse matrix
    %obslik_i = mk_ghmm_obs_lik(data, engine.obsprob{i}.mu, engine.obsprob{i}.Sigma);
    x = data(:);
    m = engine.obsprob{i}.mu(:);
    invC = engine.obsprob{i}.inv_Sigma;
    denom = engine.obsprob{i}.denom;
    numer = exp(-0.5 * (x-m)' * invC * (x-m));
    obslik_i = numer / denom;
  end
  obslik = obslik .* obslik_i;
end