Fuzzy Observable Markov Models for Pattern Recognition

Dat Tran; Wanli Ma; Dharmendra Sharma

doi:10.20965/jaciii.2007.p0662

Fuzzy Observable Markov Models for Pattern Recognition

Dat Tran
, Wanli Ma
, Dharmendra Sharma

Research output: Contribution to journal › Article › peer-review

Abstract

This paper presents a mathematical framework for fuzzy discrete and continuous observable Markov models (OMMs) and their applications to written language, spam email and typist recognition. Experimental results show that the proposed OMMs are more effective than models such as vector quantization, Gaussian mixture model and hidden Markov model

Original language	English
Pages (from-to)	662-667
Number of pages	6
Journal	Journal of Advanced Computational Intelligence and Intelligent Informatics
Volume	11
Issue number	6
DOIs	https://doi.org/10.20965/jaciii.2007.p0662
Publication status	Published - 2007

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title = "Fuzzy Observable Markov Models for Pattern Recognition",

abstract = "This paper presents a mathematical framework for fuzzy discrete and continuous observable Markov models (OMMs) and their applications to written language, spam email and typist recognition. Experimental results show that the proposed OMMs are more effective than models such as vector quantization, Gaussian mixture model and hidden Markov model",

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JO - Journal of Advanced Computational Intelligence and Intelligent Informatics

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Fuzzy Observable Markov Models for Pattern Recognition

Abstract

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