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Pinning Exponential Synchronization of Nonlinearly Coupled Neural Networks with Mixed Delays via Intermittent Control

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  • Control Theory and Applications
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Abstract

This paper is concerned with the exponential synchronization problem of nonlinearly coupled neural networks with mixed delays. By employing the intermittent control strategy, several appropriate linear and adaptive pinning controllers are designed in each control period. With the help of a new differential inequality, some conditions are proposed to guarantee that the coupled networks can realize pinning synchronization exponentially. The minimum number of pinned nodes is determined by using high-degree pinning scheme. Two numerical examples are provided finally to demonstrate the effectiveness of the theoretical results.

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Correspondence to Jian-An Wang.

Additional information

Recommended by Associate Editor Hyo-Sung Ahn under the direction of Editor Yoshito Ohta. This journal was supported by the Youth Foundation of Shanxi Province (Grant No. 201701D221107) and the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (Grant no. 2015168).

Jian-An Wang received the B.S. degree from Jiangxi Normal University, Nanchang, China, in 2005. He obtained his Ph.D. degree from University of Science and Technology Beijing, Beijing, China, in 2011. Now, he is an associate professor with the School of Electronics Information Engineering, Taiyuan University of Science and Technology. His research interests include the time-delay system, complex network and robust control.

Xin-Yu Wen received his Ph.D. degree in School of Automation from Southeast University in 2011. Now, he is an associate professor with the School of Electronics Information Engineering, Taiyuan University of Science and Technology. His research interests include nonlinear systems, robust control, and disturbance observer.

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Wang, JA., Wen, XY. Pinning Exponential Synchronization of Nonlinearly Coupled Neural Networks with Mixed Delays via Intermittent Control. Int. J. Control Autom. Syst. 16, 1558–1568 (2018). https://doi.org/10.1007/s12555-016-0046-2

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  • DOI: https://doi.org/10.1007/s12555-016-0046-2

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