Volume 4 Number 11 (Nov. 2009)
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JCP 2009 Vol.4(11): 1167-1174 ISSN: 1796-203X
doi: 10.4304/jcp.4.11.1167-1174

A Research on Mixture Splitting for CHMM Based on DBC

Gang Liu, Wei Chen, Jun Guo
Key Laboratory of Information Processing and Intelligent Technology, Beijing University of Posts and Telecommunications, Beijing, China
Abstract—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.

Index Terms—Mixture splitting, DBC, HMM, EM.

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Cite: Gang Liu, Wei Chen, Jun Guo, "A Research on Mixture Splitting for CHMM Based on DBC," Journal of Computers vol. 4, no. 11, pp. 1167-1174, 2009.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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