Global exponential stability of interval general BAM neural networks with reaction–diffusion terms and multiple time-varying delays
✍ Scribed by Zhengqiu Zhang; Yan Yang; Yesheng Huang
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 313 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0893-6080
No coin nor oath required. For personal study only.
✦ Synopsis
In this paper, we first discuss the existence and uniqueness of the equilibrium point of interval general BAM neural networks with reaction-diffusion terms and multiple time-varying delays by means of using degree theory. Then by applying the existence result of an equilibrium point and constructing a Lyapunov functional, we discuss global exponential stability for above neural networks. In the last section, we also give an example to demonstrate the validity of our global exponential stability result for above neural network.
📜 SIMILAR VOLUMES
This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the glob
In this paper, we first investigate the existence of a periodic solution to interval general bidirectional associative memory (BAM) neural networks with multiple delays on time scales by the continuation theorem of coincidence degree theory. Then, by constructing a Lyapunov functional, we discuss th