Exponential convergence for high-order recurrent neural networks with a class of general activation functions
โ Scribed by Hong Zhang; Wentao Wang; Bing Xiao
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 201 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0307-904X
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The paper presents theoretical results on the global exponential periodicity and global exponential stability of a class of recurrent neural networks with various general activation functions and time-varying delays. The general activation functions include monotone nondecreasing functions, globally
In this paper, by utilizing Lyapunov functional method, the quality of negative definite matrix and the linear matrix inequality approach, the global exponential stability of the equilibrium point for a class of generalized delayed neural networks with impulses is investigated. A new criterion on gl