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A delay-dependent asymptotic stability criterion of cellular neural networks with time-varying discrete and distributed delays
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cho, Hyun Jeong |
| Copyright Year | 2007 |
| Abstract | Based on the Lyapunov functional stability analysis for differential equations and the linear matrix inequality (LMI) optimization approach, A novel criterion for the global asymptotic stability of cellular neural networks with time-varying discrete and distributed delays is derived to guarantee global asymptotic stability. The criterion is expressed in terms of LMIs, which can be solved easily by various convex optimization algorithms. Some numerical examples are given to show the effectiveness of proposed method. 2006 Elsevier Ltd. All rights reserved. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ynucc.yu.ac.kr/~jessie/temp/jessie_csf071.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Artificial neural network Convex optimization Linear matrix inequality Lyapunov fractal Mathematical optimization Neural Network Simulation Numerical analysis Social inequality |
| Content Type | Text |
| Resource Type | Article |