Delay-dependent exponential stability for a class of neural networks with time delays and reaction-diffusion terms |
| |
| Authors: | Jianlong Qiu Jinde Cao |
| |
| Institution: | a School of Automation, Southeast University, Nanjing 210096, China
b Department of Mathematics, Linyi Normal University, Linyi 276005, China |
| |
| Abstract: | In this paper, the exponential stability of a class of delayed neural networks described by nonlinear delay differential equations of the neutral type has been studied. By constructing appropriate Lyapunov functional and using the linear matrix inequality (LMI) optimization approach, a series of sufficient criteria is obtained ensuring the existence, uniqueness and global exponential stability of an equilibrium point of such a kind of delayed neural networks. These conditions are dependent on the size of the time delay and the measure of the space, which is usually less conservative than delay-independent and space-independent ones. And, these networks are generalized without assuming the boundedness and differentiability of the activate functions. The proposed LMI condition can be checked easily by recently developed algorithms. The results are new and improve the earlier work. Examples are provided to demonstrate the effectiveness and applicability of the proposed criteria. |
| |
| Keywords: | Neural networks Reaction-diffusion Delay Neutral type Exponential stability Linear matrix inequality |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
