Variable-time impulses in BAM neural networks with delays

Authors:
Chao Liu;Chuandong Li;Xiaofeng Liao
Affiliations:
College of Computer, Chongqing University 400044, China;College of Computer, Chongqing University 400044, China;College of Computer, Chongqing University 400044, China
Venue:
Neurocomputing
Year:
2011

Citing 18
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Abstract

In this paper, the globally exponential stability of BAM neural networks with time delays and impulses has been studied. Different from most existing publications, the case of variable time impulses is dealt with in the present paper, i.e., impulse occurring is not at fixed instants but depends on the states of systems. By using Lyapunov function and inequality technique, some globally exponential stability criteria of BAM neural networks with time delays and variable-time impulses have been established. When the proposed results can also be applied to the case of fixed-time impulses, it provides new stability conditions for the case of fixed-time impulses. Numerical examples are also given to illustrate the effectiveness of our theoretical results.