On the strong convergence of the orthogonal series-type kernel regression neural networks in a non-stationary environment

Authors:
Piotr Duda;Yoichi Hayashi;Maciej Jaworski
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland;Department of Computer Science, Meiji University, Kawasaki, Japan;Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Year:
2012

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Abstract

Strong convergence of general regression neural networks is proved assuming non-stationary noise. The network is based on the orthogonal series-type kernel. Simulation results are discussed in details.