Domain of attraction on adaptive feature extraction of nonstationary processes

Authors:
Hong Chen;Ruey-wen Liu
Affiliations:
Department of Electrical Engineering, University of Notre Dame, IN;Department of Electrical Engineering, University of Notre Dame, IN
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Year:
1993

Citing 2
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Abstract

This paper first reviews briefly the procedure concerning a convergence analysis of a learning algorithm for adaptive feature extraction. It then addresses the issue of identification of a nontrivial domain of attraction for the learning system. The problem is important because such an identification is not only powerful for choosing initial settings of the system, but also holds one of the keys to the quantitative analysis of its adaptivity in an nonstationary environment. Finally, experimental results are presented.