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Phys. Rev. E 64, 051901 (2001) [13 pages]

Stability criteria for delayed neural networks

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Hongtao Lu*
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200030, People’s Republic of China

Received 3 June 2000; revised 11 May 2001; published 12 October 2001

In this paper, delay-independent global asymptotic and exponential stability for a class of delayed neural networks (DNN’s) is investigated, and some criteria are established to ensure stability of DNN’s by applying the Lyapunov direct method. These criteria are expressed by imposing constraints on weight matrices of the networks, and they are easy to verify and so are applicable in the design of DNN’s. Comparisons between our criteria and some earlier results are also made; it is shown that our results generalize some existing criteria in the literature.

© 2001 The American Physical Society

URL:
http://link.aps.org/doi/10.1103/PhysRevE.64.051901
DOI:
10.1103/PhysRevE.64.051901
PACS:
87.10.+e, 85.40.Ls, 05.45.-a, 43.80.+p

*Email address: htlu@mail1.sjtu.edu.cn