State Feedback Stabilization for Neutral-Type Neural Networks with Time-Varying Discrete and Unbounded Distributed Delays | Zendy

Yantao Wang | Zendy; Xue Lin | Zendy; Xian Zhang | Zendy

Open Access

State Feedback Stabilization for Neutral-Type Neural Networks with Time-Varying Discrete and Unbounded Distributed Delays

Author(s) -

Yantao Wang,

Xue Lin,

Xian Zhang

Publication year - 2012

Publication title -

journal of control science and engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.208

H-Index - 18

eISSN - 1687-5257

pISSN - 1687-5249

DOI - 10.1155/2012/517157

Subject(s) - linearization , nonlinear system , control theory (sociology) , artificial neural network , type (biology) , mathematics , complementarity (molecular biology) , computer science , range (aeronautics) , class (philosophy) , state (computer science) , control (management) , algorithm , engineering , artificial intelligence , ecology , physics , genetics , quantum mechanics , biology , aerospace engineering

The problem of stabilization for a class of neutral-type neural networks with discrete and unbounded distributed delays is investigated. By introducing an appropriate Lyapunov-Krasovskii functional and using Jensen inequality technique to deal with its derivative, delay-range-dependent and rate-dependent stabilization criteria are presented in the form of LMIs with nonlinear constraints. In order to solve the nonlinear problem, a cone complementarity linearization (CCL) algorithm is offered. In addition, several numerical examples are provided to illustrate the applicability of the proposed approach

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