On the uniform convergence of the orthogonal series-type kernel regression neural networks in a time-varying environment

Authors:
Meng Joo Er;Piotr Duda
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;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

Sufficient conditions for uniform convergence of general regression neural networks, based on the orthogonal series-type kernel, are given. The convergence is guarantee even if variance of noise diverges to infinity. Simulation results are presented.