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Pinning Impulsive Synchronization of Stochastic Memristor-based Neural Networks with Time-varying Delays

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Abstract

This paper investigates the exponential and asymptotical synchronization of stochastic memristor-based neural networks (SMNNs) with time-varying delays via pinning impulsive control. A novel type of pinning impulsive controllers is introduced to synchronize the master system and slave system. Based on the physical properties of memristor, the mathematical model of SMNNs is obtained by the theories of drive-response concept, set-valued maps and stochastic differential inclusions. Then some sufficient verifiable conditions are constructed for the synchronization of SMNNs by applying the Lyapunov-Krasovskii functional (LKF) method. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results.

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Correspondence to Qianhua Fu.

Additional information

Recommended by Associate Editor Ohmin Kwon under the direction of Editor Jessie (Ju H.) Park. This work was supported in part by the National Natural Science Foundation of China under Grant 61533006, in part by the Scientific Research Project of Sichuan Provincial Education Department (18ZB0572), in part by the Research Fund for International Young Scientists of National Natural Science Foundation of China under Grant 61550110248.

Qianhua Fu received the B.S. degree in electronic information engineering from Chongqing University of Technology, China, in 2003, and received the M.S. degree in communication and information systems from University of Electronic Science and Technology of China (UESTC) in 2010. He was a R&D engineer in HUAWEI company from 2010 to 2014. He is currently pursuing a Ph.D. degree in information and communication Engineering, UESTC and working as an engineer at Xihua University. His main research interests are memristor neural network, RF circuits and systems for wireless communications, and signal processing in modern communication.

Jingye Cai received the B.S. degree from Sichuan University in 1983, and the M.S. degree from the University of Electronic Science and Technology of China (UESTC) in 1990. He is currently a professor with the School of Software and Information Engineering, UESTC. His research interests include nonlinear circuits and systems (memristor), communication signal processing, RF and wireless systems.

Shouming Zhong was born on November 5, 1955. He graduated from University of Electronic Science and Technology of China (UESTC), majoring Applied Mathematics on Differential Equation. He is a professor of School of Mathematical Sciences, UESTC, since June 1997-present. He is the director of Chinese Mathematical Biology Society, the chair of Biomathematics in Sichuan, and editor of Journal of Biomathematics. His research interest is stability theorem and its application research of the differential system, the robustness control, neural network and biomathematics.

Yongbin Yu received his M.S. and Ph.D. degrees in circuits and systems from University of Electronic Science and Technology of China (UESTC), in 2004 and 2008, respectively. He is currently an associate professor with the School of Software and Information Engineering, UESTC. His current research interest covers nonlinear circuits and systems (memristor), artificial intelligence, modern control theory and its application.

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Fu, Q., Cai, J., Zhong, S. et al. Pinning Impulsive Synchronization of Stochastic Memristor-based Neural Networks with Time-varying Delays. Int. J. Control Autom. Syst. 17, 243–252 (2019). https://doi.org/10.1007/s12555-018-0295-3

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  • DOI: https://doi.org/10.1007/s12555-018-0295-3

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