4.7 Article

Global robust stability of delayed recurrent neural networks

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CHAOS SOLITONS & FRACTALS
卷 23, 期 1, 页码 221-229

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2004.04.002

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This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results. (C) 2004 Elsevier Ltd. All rights reserved.

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