On the application of the parzen-type kernel probabilistic neural network and recursive least squares method for learning in a time-varying environment

Authors:
Maciej Jaworski;Yoichi Hayashi
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland;Department of Computer Science, Meiji University, Tama-ku, Kawasaki, Japan
Venue:
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Year:
2011

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Abstract

This paper presents the Parzen kernel-type regression neural network in combination with recursive least squares method to solve problem of learning in a time-varying environment. Sufficient conditions for convergence in probability are given. Simulation experiments are presented and discussed.