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% 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

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