Robust global periodicity of interval bidirectional associative memory networks with finite distributed delays

Authors:
Xiaofan Yang;David J. Evans;Yuan Yan Tang;Xiaofeng Liao
Affiliations:
Chongqing University, College of Computer Science, Chongqing, P.R. China and Chongqing Jiaotong University, College of Computer and Information, Chongqing, P.R. China;Department of Computer Science, Loughborough University, Parallelism, Algorithms and Architectures Research Centre, Loughborough, Leicestershire, United Kingdom;Chongqing University, College of Computer Science, Chongqing, P.R. China;Chongqing University, College of Computer Science, Chongqing, P.R. China
Venue:
International Journal of Systems Science
Year:
2007

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Abstract

This article addresses the robust periodicity properties of a class of interval bidirectional associative memory networks with finite distributed delays. A set of criteria are proposed for the robust global exponential periodicity of such networks. Our results depend neither on differentiability nor on monotonicity of the activation functions of the neurons. In addition, these criteria are easily checkable.