Discrete-time recurrent neural networks with complex-valued linear threshold neurons

Authors:
Wei Zhou;Jacek M. Zurada
Affiliations:
Computational Intelligence Laboratory, Sch. of Comp. Sci. and Engineering, Univ. of Electronic Sci. and Techn. of China, Chengdu, China and Computational Intelligence Lab., Dept. of Electrical and ...;Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY
Venue:
IEEE Transactions on Circuits and Systems II: Express Briefs
Year:
2009

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Abstract

This brief discusses a class of discrete-time recurrent neural networks with complex-valued linear threshold neurons. It addresses the boundedness, global attractivity, and complete stability of such networks. Some conditions for those properties are also derived. Examples and simulation results are used to illustrate the theory.