A class of discrete-time recurrent neural networks with multivalued neurons

Authors:
Wei Zhou;Jacek M. Zurada
Affiliations:
Computational Intelligence Laboratory, School of Computer Science and Eng., Univ. of Electronic Sci. and Techn. of China, Chengdu, China and Computational Intelligence Laboratory, Electrical and C ...;Computational Intelligence Laboratory, Electrical and Computer Engineering Department, University of Louisville, Louisville, KY
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

This paper discusses a class of discrete time recurrent neural networks with multi valued neurons (MVN) with complex-valued weights and an activation function defined as a function of the argument of a weighted sum. Complementing state-of-the-art of such networks, this paper focuses on the convergence analysis of such networks in synchronous update mode. One theorem is presented and simulation results are used to illustrate the theory.