Title :
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
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;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
