Title :
Discriminative base decomposition for time-frequency matrix decomposition
Author :
Ghoraani, Behnaz ; Krishnan, Sridhar
Author_Institution :
Dept. of Electr. & Comptr. Eng., Ryerson Univ., Toronto, ON, Canada
Abstract :
Time-frequency matrix (TFM) decomposition using non-negative matrix factorization (NMF) has been recently considered as a successful tool for time-frequency (TF) quantification. In this paper, we modify the constraints of traditional cost function of NMF to make the method a better fit for TF quantification, and denote the new method with NMF discriminant base (NMFDB) decomposition. We evaluate the proposed method, and show that it successfully identifies the discriminant bases. Additionally, we measure the discrimination ability of NMFDB over the signals with very low discriminations, and compare it with the discrimination of the decomposed bases derived using traditional NMF. It is concluded that the proposed method is able to locate the region of difference with 20% better performance compared to the conventional NMF.
Keywords :
matrix decomposition; quantisation (signal); time-frequency analysis; NMF; TF quantification; discriminative base decomposition; nonnegative matrix factorization; time-frequency matrix decomposition; Cost function; Failure analysis; Feature extraction; Hydrogen; Matrix decomposition; Pattern analysis; Signal analysis; Signal detection; Signal processing; Time frequency analysis; Matrix decomposition; Pattern classification; Time-frequency analysis;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5495889