In this paper, we discuss impulsive high-order Hopfield type neural networks. Investigating their global asymptotic stability, by using Lyapunov function method, sufficient conditions that guarantee global asymptotic stability of networks are given. These criteria can be used to analyse the dynamics
Stability and periodicity in high-order neural networks with impulsive effects
โ Scribed by Haibo Gu; Haijun Jiang; Zhidong Teng
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 618 KB
- Volume
- 68
- Category
- Article
- ISSN
- 0362-546X
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โฆ Synopsis
In this paper, the global exponential stability and periodicity are investigated for a class generalized high-order neural networks with time delays and impulses; some sufficient conditions are derived for checking the global exponential stability and existence of periodic solutions for this system using the generalized Halanay inequality, mathematical induction and a fixed point theorem. The criteria given are easily verified and possess many adjustable parameters, which provides flexibility for the design and analysis of the system. Finally, an example with numerical simulation is given to show the effectiveness of the proposed method and results.
๐ SIMILAR VOLUMES
We investigate stationary oscillation for high-order Hopfield neural networks with time delays and impulses. In a recent paper [J. Zhang, Z. J. Gui, Existence and stability of periodic solutions of high-order Hopfield neural networks with impulses and delays, Journal of Computational and Applied Mat