Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/103510
Title: Local discriminant time-frequency atoms for signal classification
Authors: Jiang, Q. 
Goh, S.S. 
Lin, Z.
Keywords: Fisher's class separability
Linear discriminant analysis
Local discriminant time-frequency atoms
Signal classification
Issue Date: 1999
Citation: Jiang, Q.,Goh, S.S.,Lin, Z. (1999). Local discriminant time-frequency atoms for signal classification. Signal Processing 72 (1) : 47-52. ScholarBank@NUS Repository.
Abstract: Three methods to select discriminant time-frequency atoms from the Gabor time-frequency dictionary are proposed. The first method performs a discriminant pursuit in its selection, the second method leads to atoms with the most discriminant power, and the third method combines the first two methods. The time-frequency atoms selected by the methods extract discriminant features among different classes of signals. Experimental results on the classification of simulated data sets (triangular waveforms) and real data sets (speech signals) using the extracted features are presented. © 1999 Elsevier Science B.V. All rights reserved.
Source Title: Signal Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/103510
ISSN: 01651684
Appears in Collections:Staff Publications

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