期刊
INFORMATION SCIENCES
卷 232, 期 -, 页码 386-396出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2012.11.023
关键词
Periodic solution; Exponential stability; Memristor; Recurrent neural network; Time delay
资金
- National Science Foundation of China [11271146]
- Key Program of National Natural Science Foundation of China [61134012]
- 973 Program of China [2011CB710606]
The paper presents theoretical results on the global exponential periodicity and stability of a class of memristor-based recurrent neural networks with multiple delays. The dynamic analysis in the paper employs the theory of differential equations with discontinuous right-hand side as introduced by Filippov. By using the inequality techniques and a useful Lyapunov functional, some new testable algebraic criteria are obtained for ensuring the existence and global exponential stability of periodic solution of the system. The model based on the memristor widens the application scope for the design of neural networks, and the new effective results also enrich the toolbox for the qualitative analysis of neural networks. (C) 2012 Elsevier Inc. All rights reserved.
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