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| | [No title] (Site not responding. Last check: 2007-11-01) |
 | | function [LL, prior, transmat, obsmat] = dhmm_em(data, prior, transmat, obsmat, varargin) % LEARN_DHMM Find the ML/MAP parameters of an HMM with discrete outputs using EM. |
 | | % [ll_trace, prior, transmat, obsmat] = learn_dhmm(data, prior0, transmat0, obsmat0,...) % % Notation: Q(t) = hidden state, Y(t) = observation % % INPUTS: % data{ex} or data(ex,:) if all sequences have the same length % prior(i) % transmat(i,j) % obsmat(i,o) % % Optional parameters may be passed as 'param_name', param_value pairs. |
 | | compute_ess_dhmm(startprob, transmat, obsmat, data, dirichlet) % COMPUTE_ESS_DHMM Compute the Expected Sufficient Statistics for an HMM with discrete outputs % function [loglik, exp_num_trans, exp_num_visits1, exp_num_emit, exp_num_visitsT] =... |
| www.cs.toronto.edu /pub/psala/Project/HMM/dhmm_em.m (222 words) |
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