Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1864343 | Physics Letters A | 2009 | 7 Pages |
Abstract
This Letter investigates the problem of exponential stability for discrete stochastic time-delay neural networks. By defining a novel Lyapunov functional, an improved delay-dependent exponential stability criterion is established in terms of linear matrix inequality (LMI) approach. Meanwhile, the computational complexity of the newly established stability condition is reduced because less variables are involved. Numerical example is given to illustrate the effectiveness and the benefits of the proposed method.
Keywords
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Physical Sciences and Engineering
Physics and Astronomy
Physics and Astronomy (General)
Authors
Zhengguang Wu, Hongye Su, Jian Chu, Wuneng Zhou,