Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
408391 | Neurocomputing | 2007 | 16 Pages |
Abstract
Some delay-dependent robust asymptotical stability criteria for uncertain linear time-variant systems with multiple delays are established by means of parameterized first-order model transformation and the transformation of the interval uncertainty into the norm-bounded uncertainty. The stable regions with respect to the delay parameters are also formulated. Based on these results, we investigate the stability issue of a class of delayed neural networks that can be transformed into linear time-variant systems, and then several new global asymptotical stability criteria are exploited. Numerical examples are presented to illustrate the effectiveness of our results.
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhong Zhang, Chuandong Li, Xiaofeng Liao,