On the structure of hidden Markov models

被引：18

作者：

Abou-Moustafa, KT

Cheriet, M

Suen, CY

机构：

[1] Concordia Univ, Dept Comp Sci, CENPARMI, Montreal, PQ H3G 1M8, Canada

[2] Univ Quebec, Ecole Technol Super, LIVIA, Montreal, PQ H3C 1K3, Canada

来源：

PATTERN RECOGNITION LETTERS | 2004年 / 25卷 / 08期

基金：

加拿大自然科学与工程研究理事会;

关键词：

HMM structure; graphical models; credits diffusion; Ocham's razor; K-means clustering;

D O I：

10.1016/j.patrec.2004.02.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the effect of HMM structure on the performance of HMM-based classifiers. The investigation is based on the framework of graphical models, the diffusion of credits of HMMs and empirical experiments. Although some researchers have focused on determining the number of states, this study shows that the topology has a stronger influence on increasing the performance of HMM-based classifiers than the number of states. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：923 / 931

页数：9

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