DocumentCode
1071339
Title
Optimized support vector machines for nonstationary signal classification
Author
Davy, Manuel ; Gretton, Arthur ; Doucet, Arnaud ; Rayner, Peter J W
Author_Institution
Inst. de Recherche en Commun. et Cybernetique de Nantes, France
Volume
9
Issue
12
fYear
2002
Firstpage
442
Lastpage
445
Abstract
This letter describes an efficient method to perform nonstationary signal classification. A support vector machine (SVM) algorithm is introduced and its parameters optimized in a principled way. Simulations demonstrate that our low-complexity method outperforms state-of-the-art nonstationary signal classification techniques.
Keywords
computational complexity; learning automata; signal classification; SVM algorithm; low-complexity method; nonstationary signal; nonstationary signal classification; optimized support vector machines; Acoustic measurements; Associate members; Classification algorithms; Frequency domain analysis; Kernel; Pattern classification; Support vector machine classification; Support vector machines; Time frequency analysis;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2002.806070
Filename
1159634
Link To Document