In this paper, by utilizing the Lyapunov functionals, the analysis method and the impulsive control, we analyze the exponential stability of Hopfield neural networks with time-varying delays. A new criterion on the exponential stabilization by impulses and the exponential stabilization by periodic i
Exponential stability of Hopfield neural networks with impulses
โ Scribed by Benedetta Lisena
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 219 KB
- Volume
- 12
- Category
- Article
- ISSN
- 1468-1218
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
In this paper, by means of constructing the extended impulsive delayed Halanay inequality and by Lyapunov functional methods, we analyze the global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays. Some new sufficient conditions ensuring exponentia
The stability of stochastic delayed Hopfield neural networks (DHNN) is investigated in this paper. Under the help of suitable Lyapunov function and the semimartingale convergence theorem, we obtain some sufficient criteria to check the almost sure exponential stability of the DHNN.
In this paper, we consider the uniform asymptotic stability, global asymptotic stability and global exponential stability of the equilibrium point of Hopfield neural networks with delays and impulsive perturbation. Some new stability criteria for such system are derived by using the Lyapunov functio
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