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Global asymptotic stability of stochastic Cohen–Grossberg-type BAM neural networks with mixed delays: An LMI approach

✍ Scribed by Xiaodi Li; Xilin Fu

Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
280 KB
Volume
235
Category
Article
ISSN
0377-0427

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✦ Synopsis

In this paper, we consider the stochastic Cohen-Grossberg-type BAM neural networks with mixed delays. By utilizing the Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) approach, some sufficient LMI-based conditions are obtained to guarantee the global asymptotic stability of stochastic Cohen-Grossberg-type BAM neural networks with mixed delays. These conditions can be easily checked via the MATLAB LMI toolbox. Moreover, the obtained results extend and improve the earlier publications. Finally, a numerical example is provided to demonstrate the low conservatism and effectiveness of the proposed LMI conditions.

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