Improved Global Exponential Stability Criterion for BAM Neural Networks with Time-Varying Delays

Authors:
Yonggang Chen;Tiheng Qin
Affiliations:
Department of Mathematics, Henan Institute of Science and Technology, , Xinxiang, China 453003;Department of Basic Courses, Henan Mechanical and Electrical Engineering College, , Xinxiang, China 453002
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Year:
2008

Citing 5
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Abstract

In this paper, the global exponential stability analysis is investigated for a class of bidirectional associative memory (BAM) neural networks with time-varying delays. By using Lyapunov functional method, and by reserving the useful terms when estimating the upper bound of the derivative of Lyapunov functional, the less conservative exponential stability criterion is derived in terms of linear matrix inequality (LMI). Numerical example is presented to show the effectiveness and the less conservativeness of the proposed method.