Biosignal pattern recognition and interpretation systems. 3. Methods of classification

Author

Ciaccio, E.J. ; Dunn, S.M. ; Akay, M.

Author_Institution

Dept. of Biomed. Eng., Rutgers Univ., New Brunswick, NJ, USA

Volume

13

Issue

1

fYear

1994

Firstpage

129

Lastpage

135

Abstract

The following topics are discussed: Bayes/minimum distance classifiers; maximum likelihood classification estimation; k-nearest neighbor classification; entropy criteria; syntactic techniques; string matching; the Cocke-Younger-Kasami parsing algorithm; syntactic learning; finite-state automata; neural network classification techniques; learning vector quantization; cluster swapping; hierarchial clustering procedures.<>

Keywords

Bayes methods; finite automata; medical signal processing; neural nets; pattern recognition; Bayes classifiers; Cocke-Younger-Kasami parsing algorithm; biosignal interpretation system; biosignal pattern recognition; classification methods; cluster swapping; entropy criteria; finite-state automata; hierarchial clustering procedures; k-nearest neighbor classification; learning vector quantization; maximum likelihood classification estimation; minimum distance classifiers; neural network classification techniques; string matching; syntactic learning; syntactic techniques; Biomedical engineering; Covariance matrix; Equations; Euclidean distance; Matched filters; Maximum likelihood estimation; Noise reduction; Nonlinear filters; Pattern recognition; Vectors;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.265792

Filename

265792