New Results for Periodic Solution of High-Order BAM Neural Networks with Continuously Distributed Delays and Impulses | Zendy

Chang-Bo Yang | Zendy; TingZhu Huang | Zendy; Jinliang Shao | Zendy

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New Results for Periodic Solution of High-Order BAM Neural Networks with Continuously Distributed Delays and Impulses

Author(s) -

Chang-Bo Yang,

TingZhu Huang,

Jinliang Shao

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/247046

Subject(s) - uniqueness , correctness , exponential stability , artificial neural network , control theory (sociology) , mathematics , computer science , stability (learning theory) , order (exchange) , linear matrix inequality , lyapunov function , mathematical optimization , mathematical analysis , algorithm , control (management) , artificial intelligence , nonlinear system , physics , finance , quantum mechanics , machine learning , economics

By M-matrix theory, inequality techniques, and Lyapunov functional method, certain sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of periodic solution for a new type of high-order BAM neural networks with continuously distributed delays and impulses. These novel conditions extend and improve some previously known results in the literature. Finally, an illustrative example and its numerical simulation are given to show the feasibility and correctness of the derived criteria

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