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Content Provider | IEEE Xplore Digital Library |
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Author | Wu-Hua Chen Xiaomei Lu Zhi-Hong Guan Wei Xing Zheng |
Copyright Year | 2005 |
Description | Author affiliation: Coll. of Math. & Inf. Sci., Guangxi Univ., Nanning (Wu-Hua Chen; Xiaomei Lu) |
Abstract | This paper focuses on the problem of delay- dependent stability analysis of neural networks with variable delay. Two types of variable delay are considered: one is differentiable and has bounded derivative; the other one is continuous and may vary very fast. By introducing a new type of Lyapunov-Krasovskii functional, new delay-dependent sufficient conditions for exponential stability of delayed neural networks are derived in terms of linear matrix inequalities. We also obtain delay-independent stability criteria. These criteria can be tested numerically and very efficiently using interior point algorithms. Two examples are presented which show our results are less conservative than the existing stability criteria. |
Starting Page | 1 |
Ending Page | 6 |
File Size | 100851 |
Page Count | 6 |
File Format | |
ISBN | 0780393112 |
DOI | 10.1109/TENCON.2005.301280 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-11-21 |
Publisher Place | Australia |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Stability analysis Neural networks Sufficient conditions Delay effects Stability criteria Linear matrix inequalities Lyapunov method Artificial neural networks Convergence Circuit stability delay-dependent criteria Neural Networks variable delay linear matrix inequality (LMI) exponential stability |
Content Type | Text |
Resource Type | Article |
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