Loading...
|
Please use this identifier to cite or link to this item:
http://ir.ncue.edu.tw/ir/handle/987654321/13713
|
| Title: | Delay- Dependent Approach to Robust Stability for Uncertain Discrete Stochastic Recurrent Neural Networks with Interval Time-Varying Delays |
| Authors: | Lu, Chien-Yu;Zheng, Kai-Yuan;Liao, Chin-Wen;Huang, Chuan-Kuei;Pan, Po-Jung |
| Contributors: | 工業教育與技術學系 |
| Keywords: | Discrete stochastic recurrent neural network;Interval time-varying delay;Linear matrix inequality;Uncertainty;Robust stability |
| Date: | 2008-11
|
| Issue Date: | 2012-08-27T10:47:26Z
|
| Publisher: | National Cheng Kung University |
| Abstract: | This paper considers the problem of global robust delay-range-dependent stability for uncertain discrete stochastic recurrent neural networks with interval time-varying delays. The parameter uncertainties are assumed to be time-varying norm-bounded in the state equation. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate Lyapunov- Krasovskii functional, global robust delay-dependent stability criterion which is dependent on both the lower bound and upper bound of the interval time-varying delays is derived. A sufficient condition for the discrete stochastic recurrent neural networks with interval time-varying delays is presented in terms of the linear matrix inequality (LMI). An example is given to demonstrate the reduced conservatism of the proposed results in this paper. |
| Relation: | Proceedings of 2008 CACS International Automatic Control Conference, National Cheng Kung University, Tainan, Taiwan, 2008年11月21-23日 |
| Appears in Collections: | [工業教育與技術學系] 會議論文
|
Files in This Item:
| File |
Size | Format | |
|---|
| 2030100916003.pdf | 34Kb | Adobe PDF | 417 | View/Open |
|
All items in NCUEIR are protected by copyright, with all rights reserved.
|
