文件名称:HMM
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mm_em.m
function [LL, prior, transmat, obsmat, nrIterations] = ...
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, iterNr] = learn_dhmm(data, prior0, transmat0, obsmat0, ...)
Notation: Q(t) = hidden state, Y(t) = observation
INPUTS:-mm_em.m function [LL, prior, transmat, obsmat, nrIterations] = ... 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, iterNr] = learn_dhmm (data, prior0, transmat0, obsmat0, ...) Notation: Q (t) = hidden state, Y (t) = observation INPUTS:
function [LL, prior, transmat, obsmat, nrIterations] = ...
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, iterNr] = learn_dhmm(data, prior0, transmat0, obsmat0, ...)
Notation: Q(t) = hidden state, Y(t) = observation
INPUTS:-mm_em.m function [LL, prior, transmat, obsmat, nrIterations] = ... 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, iterNr] = learn_dhmm (data, prior0, transmat0, obsmat0, ...) Notation: Q (t) = hidden state, Y (t) = observation INPUTS:
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下载文件列表
HMM.txt