期刊
NEURAL NETWORKS
卷 63, 期 -, 页码 48-56出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2014.10.011
关键词
Memristor; Neural networks; Stabilization
资金
- Natural Science Foundation of China [61125303, 61403152, 61402218]
- National Basic Research Program of China (973 Program) [2011CB710606]
- Program for Science and Technology in Wuhan of China [2014010101010004]
- Program for Changjiang Scholars and Innovative Research Team in University of China [IRT1245]
- NPRP grant from the Qatar National Research Fund (a member of Qatar Foundation) [4-1162-1-181]
This paper addresses the problem of circuit design and global exponential stabilization of memristive neural networks with time-varying delays and general activation functions. Based on the Lyapunov-Krasovskii functional method and free weighting matrix technique, a delay-dependent criteria for the global exponential stability and stabilization of memristive neural networks are derived in form of linear matrix inequalities (LMIs). Two numerical examples are elaborated to illustrate the characteristics of the results. It is noteworthy that the traditional assumptions on the boundness of the derivative of the time-varying delays are removed. (C) 2014 Elsevier Ltd. All rights reserved.
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