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hmm的matlab原码和hmm相关资料

% HMMBOX, version 3.3, Iead Rezek, Oxford University, February 2001
% Matlab toolbox for Max. Aposteriori estimation of Hidden Markov Models
%
% (Adapted from Hidden Markov Toolbox
% Version 3.2  01-Oct-99
% Copyright (c) by William Penny, Imperial College, London)
%
% hmminit          initialise Gaussian observation HMM
% hmmtrain         train HMM
% hmmdecode        make classifications using HMM
%
% obsinit          initialise observation model
% obslike          calculate likelihood of data given observation model
% obsupdate        update parameters of observation model
%
% Auxiliary routines
%
% rsum        - row sum of matrix
% rprod       - row product of matrix and vector
% rdiv        - row division of matrix by vector
%
% Other routines
%
% wgmmem      - weighted EM algorithm for training Gaussuan Mixture Models
%
% Demonstrations
% 
% demlike     - Likelihood HMM trained on synthetic time series
% demgausshmm - Gaussian observation HMM trained on synthetic time series
% demgausshmm2 - tracking a synthetic time series with Gaussian observation
%               HMM
% sleepdemo   - modelling sleep stages with Gaussian observation HMM