Generalized Projective Synchronization between Two Different Neural Networks with Mixed Time Delays | Zendy

Xuefei Wu | Zendy; Chen Xu | Zendy; Jianwen Feng | Zendy; Yi Zhao | Zendy; Zhou Xuan | Zendy

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Generalized Projective Synchronization between Two Different Neural Networks with Mixed Time Delays

Author(s) -

Xuefei Wu,

Chen Xu,

Jianwen Feng,

Yi Zhao,

Zhou Xuan

Publication year - 2012

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2012/153542

Subject(s) - invariance principle , nonlinear system , artificial neural network , control theory (sociology) , synchronization (alternating current) , global positioning system , lyapunov stability , computer science , controller (irrigation) , stability (learning theory) , lyapunov function , mathematics , topology (electrical circuits) , control (management) , artificial intelligence , machine learning , telecommunications , philosophy , linguistics , physics , quantum mechanics , combinatorics , agronomy , biology

The generalized projective synchronization (GPS) between two different neural networks with nonlinear coupling and mixed time delays is considered. Several kinds of nonlinear feedback controllers are designed to achieve GPS between two different such neural networks. Some results for GPS of these neural networks are proved theoretically by using the Lyapunov stability theory and the LaSalle invariance principle. Moreover, by comparison, we determine an optimal nonlinear controller from several ones and provide an adaptive update law for it. Computer simulations are provided to show the effectiveness and feasibility of the proposed methods

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