On the weak convergence of the orthogonal series-type kernel regresion neural networks in a non-stationary 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:
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Year:
2011

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Abstract

In the paper general regression neural networks, based on the orthogonal series-type kernel, is studied. Convergence in probability is proved assuming non-stationary noise. The performance is investigated using syntetic data.