Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4632115 | Applied Mathematics and Computation | 2010 | 8 Pages |
Abstract
The global robust asymptotic stability of bi-directional associative memory (BAM) neural networks with constant or time-varying delays and impulse is studied. An approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI) is taken to study the problem. Some a criteria for the global robust asymptotic stability, which gives information on the delay-dependent property, are derived. Some illustrative examples are given to demonstrate the effectiveness of the obtained results.
Keywords
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Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Qinghua Zhou, Li Wan,