In this paper, we study the problem of global exponential stability for cellular neural networks (CNN) with time-varying delays and fixed moments of impulsive effect. We establish several stability criteria by employing Lyapunov functions and the Razumikhin technique.
On global exponential stability for impulsive cellular neural networks with time-varying delays
โ Scribed by Ivanka M. Stamova; Rajcho Ilarionov
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 295 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0898-1221
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โฆ Synopsis
In this paper, the problem of global exponential stability for cellular neural networks (CNNs) with time-varying delays and fixed moments of impulsive effect is studied. A new sufficient condition has been presented ensuring the global exponential stability of the equilibrium points by using piecewise continuous Lyapunov functions and the Razumikhin technique combined with Young's inequality. The results established here extend those given previously in the literature. Compared with the method of Lyapunov functionals as in most previous studies, our method is simpler and more effective for stability analysis.
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