Robust stability analysis of delayed Takagi-Sugeno fuzzy Hopfield neural networks with discontinuous activation functions |
| |
| Authors: | Xiru Wu Yaonan Wang Lihong Huang Yi Zuo |
| |
| Affiliation: | (1) College of Electric and Information Technology, Hunan University, 410082 Changsha, Hunan, People’s Republic of China;(2) College of Mathematics and Econometrics, Hunan University, 410082 Changsha, Hunan, People’s Republic of China;(3) School of Energy and Power Engineering, Changsha University of Science and Technology, 410004 Changsha, Hunan, People’s Republic of China |
| |
| Abstract: | In this paper, the global robust stability problem of delayed Takagi–Sugeno fuzzy Hopfield neural networks with discontinuous activation functions (TSFHNNs) is considered. Based on Lyapunov stability theory and M-matrices theory, we derive a stability criterion to guarantee the global robust stability of TSFHNNs. Compared with the existing literature, we remove the assumptions on the neuron activations such as Lipschitz conditions, bounded, monotonic increasing property or the assumption that the right-limit value is bigger than the left one at the discontinuous point. Finally, two numerical examples are given to show the effectiveness of the proposed stability results. |
| |
| Keywords: | |
| 本文献已被 PubMed SpringerLink 等数据库收录！ |
|
