PittsburghV1, Main, Exploration, bibRecord, 000586

Circuit design and exponential stabilization of memristive neural networks.

Identifieur interne : 000586 ( Main/Exploration ); précédent : 000585; suivant : 000587

Circuit design and exponential stabilization of memristive neural networks.

Auteurs : Shiping Wen [République populaire de Chine] ; Tingwen Huang [Qatar] ; Zhigang Zeng [République populaire de Chine] ; Yiran Chen [États-Unis] ; Peng Li [États-Unis]

Source :

Neural networks : the official journal of the International Neural Network Society [ 1879-2782 ] ; 2015.

RBID : pubmed:25481670

Descripteurs français

KwdFr :
- Algorithmes, Dynamique non linéaire, Réseaux neuronaux (ordinateur).
MESH :
- Algorithmes, Dynamique non linéaire, Réseaux neuronaux (ordinateur).

English descriptors

KwdEn :
- Algorithms, Neural Networks (Computer), Nonlinear Dynamics.
MESH :
- Algorithms, Neural Networks (Computer), Nonlinear Dynamics.

Abstract

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.

DOI: 10.1016/j.neunet.2014.10.011
PubMed: 25481670

Affiliations:

Le document en format XML

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<affiliation wicri:level="1"><nlm:affiliation>Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: wenshiping226@126.com.</nlm:affiliation>
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<front><div type="abstract" xml:lang="en">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.</div>
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Circuit design and exponential stabilization of memristive neural networks.

Circuit design and exponential stabilization of memristive neural networks.

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

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