New delay-dependent exponential stability criteria of BAM neural networks with time delays

Degang Yang, Xiaofeng Liao, Chunyan Hu and Yong Wang

Mathematics and Computers in Simulation (MATCOM), 2009, vol. 79, issue 5, 1679-1697

Abstract: In this paper, the global exponential stability is investigated for the bi-directional associative memory networks with time delays. Several new sufficient conditions are presented to ensure global exponential stability of delayed bi-directional associative memory neural networks based on the Lyapunov functional method as well as linear matrix inequality technique. To the best of our knowledge, few reports about such “linearization” approach to exponential stability analysis for delayed neural network models have been presented in literature. The method, called parameterized first-order model transformation, is used to transform neural networks. The obtained conditions show to be less conservative and restrictive than that reported in the literature. Two numerical simulations are also given to illustrate the efficiency of our result.

Keywords: Exponential stability; Bi-directional associative memory neural networks; Linear matrix inequality; Time delays; Parameterized first-order model transformation (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:79:y:2009:i:5:p:1679-1697

DOI: 10.1016/j.matcom.2008.08.014

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