Discriminant non-stationary signal features’ clustering using hard and fuzzy cluster labeling

Current approaches to improve the pattern recognition performance mainly focus on either extracting non-stationary and discriminant features of each class, or employing complex and nonlinear feature classifiers. However, little attention has been paid to the integration of these two approaches. Comb...

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Bibliographic Details
Published in:	EURASIP journal on advances in signal processing Vol. 2012; no. 1; pp. 1 - 20
Main Authors:	Ghoraani, Behnaz, Krishnan, Sridhar
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 27.11.2012
Subjects:	Advances in Nonstationary Electrophysiological Signal Analysis and Processing Algorithms Classifiers Clustering Engineering Feature extraction Fuzzy Labels Marking Pattern recognition Quantum Information Technology Signal,Image and Speech Processing Spintronics Discriminant cluster selection means clustering The self-organizing tree map (SOTM) Time–frequency feature analysis Supervised classification Unsupervised clustering
ISSN:	1687-6180, 1687-6180
Online Access:	Get full text
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