Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control | Zendy

Jianwen Feng | Zendy; Siya Chen | Zendy; Jingyi Wang | Zendy; Yi Zhao | Zendy

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Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control

Author(s) -

Jianwen Feng,

Siya Chen,

Jingyi Wang,

Yi Zhao

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2836142

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper formulates the models of systems of nonlinearly and diffusively coupled memristive neural networks (CMNNs) with time-varying delays and then investigates its dynamic behaviors. Particularly, a simple yet a generic sufficient condition for quasi-synchronization of drive-response CMNNs is derived based on the Lyapunov functional methods and matrix theories. The main result shows that quasi-synchronization of such CMNNs is guaranteed by suitably designing the memsitive mechanism, the coupling matrix, and the pinning control strategy. In addition, some applicable corollaries derived from the main result are drawn by considering other circumstances, such as the linearly coupling functions, the adjustable coupling strengths, the number of controlled nodes, and so on. Finally, some numerical simulations are presented to demonstrate the effectiveness of the results.

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