New sufficient conditions for global asymptotic stability of Cohen–Grossberg neural networks with time-varying delays
| Autor: | Man-Chun Tan, Yu-Nong Zhang |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Equilibrium point
Class (set theory) Mathematical optimization Artificial neural network Applied Mathematics General Engineering Monotonic function General Medicine Computational Mathematics Lyapunov functional Exponential stability Applied mathematics Uniqueness General Economics Econometrics and Finance Analysis Mathematics |
| Zdroj: | Nonlinear Analysis: Real World Applications. 10:2139-2145 |
| ISSN: | 1468-1218 |
| DOI: | 10.1016/j.nonrwa.2008.03.022 |
| Popis: | In this paper, a class of Cohen–Grossberg neural networks with time-varying delays are considered. Without assuming the boundedness and monotonicity of activation functions, we establish new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for such delayed Cohen–Grossberg neural networks. Numerical examples are provided to show that the proposed criteria are less conservative than some results in the literature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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