Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
410902 | Neurocomputing | 2006 | 7 Pages |
Abstract
In this paper, the global robust asymptotic stability of a class of delayed bi-directional associative memory (BAM) neural networks, which contain variable uncertain parameters whose values are unknown but bounded, is studied. Some new sufficient conditions are presented for the global stability of BAM neural networks with time-varying delays by constructing Lyapunov functional and using linear matrix inequality (LMI), Halanay's inequality. A numerical example is presented to illustrate the effectiveness of our theoretical results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xuyang Lou, Baotong Cui,