A Novel Method for Decoding Any High-Order Hidden Markov Model

被引：6

作者：

Ye, Fei ^{[1
,2
]}

Wang, Yifei ^{[3
]}

机构：

[1] Nanjing Univ, Computat Expt Ctr Social Sci, Nanjing 210093, Jiangsu, Peoples R China

[2] Tongling Univ, Sch Math & Comp Sci, Tongling 244061, Anhui, Peoples R China

[3] Shanghai Univ, Dept Math, Shanghai 200444, Peoples R China

来源：

DISCRETE DYNAMICS IN NATURE AND SOCIETY | 2014年 / 2014卷

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1155/2014/231704

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar's transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.

引用

页数：6

共 20 条

[1] Mixed hidden Markov models: An extension of the hidden Markov model to the longitudinal data setting [J].

Altman, Rachel MacKay .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2007, 102 (477) :201-210

[2] Online handwritten shape recognition using segmental hidden Markov models [J].

Artieres, Thierry ;

Marukatat, Sanparith ;

Gallinari, Patrick .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2007, 29 (02) :205-217

[3] STATISTICAL INFERENCE FOR PROBABILISTIC FUNCTIONS OF FINITE STATE MARKOV CHAINS [J].

BAUM, LE ;

PETRIE, T .

ANNALS OF MATHEMATICAL STATISTICS, 1966, 37 (06) :1554-&

[4] What HMMs can do [J].

Bilmes, JA .

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2006, E89D (03) :869-891

[5] Efficient training of high-order hidden Markov models using first-order representations [J].

du Preez, JA .

COMPUTER SPEECH AND LANGUAGE, 1998, 12 (01) :23-39

[6] Efficient backward decoding of high-order hidden Markov models [J].

Engelbrecht, H. A. ;

du Preez, J. A. .

PATTERN RECOGNITION, 2010, 43 (01) :99-112

[7] Hidden Markov processes [J].

Ephraim, Y ;

Merhav, N .

IEEE TRANSACTIONS ON INFORMATION THEORY, 2002, 48 (06) :1518-1569

[8] The Application of Hidden Markov Models in Speech Recognition [J].

Gales, Mark ;

Young, Steve .

FOUNDATIONS AND TRENDS IN SIGNAL PROCESSING, 2007, 1 (03) :195-304

[9] HIGH-ORDER HIDDEN MARKOV MODELS - ESTIMATION AND IMPLEMENTATION [J].

Hadar, Uri ;

Messer, Hagit .

2009 IEEE/SP 15TH WORKSHOP ON STATISTICAL SIGNAL PROCESSING, VOLS 1 AND 2, 2009, :249-252

[10] HMM based on-line handwriting recognition [J].

Hu, JY ;

Brown, MK ;

Turin, W .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1996, 18 (10) :1039-1045

← 1 2 →