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On Global Exponential Stability for Cellular Neural Networks with Time-varying Delays
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kwon, O. M. Park, Ju H. |
| Abstract | In this paper, we consider the global exponential stability of cellular neural networks with time-varying delays. Based on the Lyapunov function method and convex optimization approach, a novel delaydependent criterion of the system is derived in terms of LMI (linear matrix inequality). In order to solve effectively the LMI convex optimization problem, the interior point algorithm is utilized in this work. Two numerical examples are given to show the effectiveness of our results. AMS Mathematics Subject Classification : 34D20, 93D05. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ynucc.yu.ac.kr/~jessie/temp/jami08.pdf |
| Alternate Webpage(s) | https://pdfs.semanticscholar.org/9b2a/608d42205158661b056b8f26e3a5c2dd88d0.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | ABLEPHARON-MACROSTOMIA SYNDROME Algorithm Convex optimization Interior point method Linear matrix inequality Lyapunov fractal Mathematical optimization Mathematics Subject Classification Neural Networks Numerical analysis Optimization problem Social inequality VHDL-AMS exponential |
| Content Type | Text |
| Resource Type | Article |
