%0 Journal Article
%T A Research on Mixture Splitting for CHMM Based on DBC
%A Gang Liu
%A Wei Chen
%A Jun Guo
%J Journal of Computers
%D 2009
%I Academy Publisher
%R 10.4304/jcp.4.11.1167-1174
%X EM (expectation-maximization) algorithm is a classical method for parameter estimation of HMM (Hidden Markov model). Concerning that EM algorithm is easily affected by initial parameter values, a mixture splitting algorithm based on decision boundary confusion(DBC) was proposed to describe more about boundary distribution. The algorithm mainly includes four aspects: firstly the number of incremented mixtures for every decision boundary could be determined according to decision boundary confusion; secondly the mixtures which are the closest to the decision boundary are chosen to split; thirdly the split mean of mixture is in the direction of decision boundary; finally the mixture number of a state is determined by the confusion between states. Our experiments show that our proposed algorithm is more effective for classification using HMM.
%K mixture splitting
%K DBC
%K HMM
%K EM
%U http://ojs.academypublisher.com/index.php/jcp/article/view/837