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Global robust stability of delayed recurrent neural networks. (English) Zbl 1075.68070

Summary: 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.

MSC:

68T05 Learning and adaptive systems in artificial intelligence
93D09 Robust stability
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