Circuit design and exponential stabilization of memristive neural networks

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...

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Bibliographic Details
Published in:Neural networks 2015-03, Vol.63, p.48-56
Main Authors: Wen, Shiping, Huang, Tingwen, Zeng, Zhigang, Chen, Yiran, Li, Peng
Format: Article
Language:English
Subjects:
Activation
Algorithms
Circuit design
Criteria
Delay
Derivatives
Mathematical analysis
Mathematical models
Memristor
Neural networks
Neural Networks (Computer)
Nonlinear Dynamics
Stabilization
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Summary: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. •Design a class of memristive neural networks with time-varying delays and general activation functions.•Investigate the exponential stabilization problem of such systems.•Set up a delay-dependent criteria for the global exponential stability and stabilization of memristive neural networks.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2014.10.011