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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	EURASIP journal on advances in signal processing Ročník 2012; číslo 1; s. 1 - 20
Hlavní autoři:	Ghoraani, Behnaz, Krishnan, Sridhar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 27.11.2012
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!