Synchronization of Switched Complex Bipartite Neural Networks with Infinite Distributed Delays and Derivative Coupling | Zendy

Qiuxiang Bian | Zendy; Jinde Cao | Zendy; Jie Wu | Zendy; Hongxing Yao | Zendy; Tingfang Zhang | Zendy; Xiaoxu Ling | Zendy

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Synchronization of Switched Complex Bipartite Neural Networks with Infinite Distributed Delays and Derivative Coupling

Author(s) -

Qiuxiang Bian,

Jinde Cao,

Jie Wu,

Hongxing Yao,

Tingfang Zhang,

Xiaoxu Ling

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/728606

Subject(s) - bipartite graph , synchronization (alternating current) , mathematics , coupling (piping) , artificial neural network , derivative (finance) , control theory (sociology) , complex network , matrix (chemical analysis) , linear matrix inequality , topology (electrical circuits) , computer science , mathematical optimization , control (management) , discrete mathematics , combinatorics , artificial intelligence , mechanical engineering , graph , materials science , financial economics , engineering , economics , composite material

A new model of switched complex bipartite neural network (SCBNN) with infinite distributed delays and derivative coupling is established. Using linear matrix inequality (LMI) approach, some synchronization criteria are proposed to ensure the synchronization between two SCBNNs by constructing effective controllers. Some numerical simulations are provided to illustrate the effectiveness of the theoretical results obtained in this paper

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