期刊
PHYSICA D-NONLINEAR PHENOMENA
卷 199, 期 3-4, 页码 425-436出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physd.2004.09.012
关键词
high-order neural networks; exponential stability; bidirectional associative memory (BAM); time delays; linear matrix inequality; Lyapunov functional
In this paper, exponential stability is studied for a class of high-order bidirectional associative memory (BAM) neural networks with time delays. By employing the linear matrix inequality (LMI) and the Lyapunov functional methods, several sufficient conditions are obtained for ensuring the system to be globally exponentially stable. Two illustrative examples are also given in the end of this paper to show the effectiveness of our results. (C) 2004 Elsevier B.V. All rights reserved.
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