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Fixed-time Synchronization of Memristive Cohen-Grossberg Neural Networks with Impulsive Effects

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  • Control Theory and Applications
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Abstract

This paper investigates the fixed-time synchronization of memristive Cohen-Grossberg neural networks with impulsive effects. Through a nonlinear transformation and Fillipov discontinuous theory, we obtain an equivalent system from the original memristive Cohen-Grossberg neural networks. By constructing a discontinuous Lyapunov function and utilizing comparison principle, a sufficient condition is achieved to guarantee the fixed-time synchronization of drive-response system with impulsive effects. Moreover, for the purpose of reducing the cost of control, an adaptive control strategy is considered. Finally, corresponding numerical simulations are carried out to show the effectiveness of the analytic results.

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Authors and Affiliations

  1. Center for Complex Systems and Network Sciences, and School of Mathematics, Southeast University, Nanjing, 210096, China

    Ruoyu Wei

  2. School of Mathematics, Southeast University, Nanjing, 210096, China

    Jinde Cao

  3. School of Electrical Engineering, Nantong University, Nantong, 226000, China

    Jinde Cao

  4. School of Mathematical Sciences, Shandong Normal University, Ji’nan, 250014, China

    Jinde Cao

  5. Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of Mathematics, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Ahmed Alsaedi

Authors
  1. Ruoyu Wei
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  2. Jinde Cao
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  3. Ahmed Alsaedi
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Corresponding author

Correspondence to Jinde Cao.

Additional information

Recommended by Associate Editor Ohmin Kwon under the direction of Editor Jessie (Ju H.) Park. This work was supported by the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence under Grant No. BM2017002.

Ruoyu Wei received the M.S. degree in applied mathematics from Southeast university, Nanjing, China. He is currently pursuing the Ph.D. degree with Southeast university, Nanjing, China. His current research interests include neural networks, multiagent systems and control theory.

Jinde Cao received the Ph.D. degree in applied mathematics from Sichuan University, Chengdu, China, in 1998. He is an Endowed Chair Professor, the Dean of School of Mathematics and the Director of the Research Center for Complex Systems and Network Sciences at Southeast University. From March 1989 to May 2000, he was with the Yunnan University. In May 2000, he joined the School of Mathematics, Southeast University, Nanjing, China. From July 2001 to June 2002, he was a Postdoctoral Research Fellow at Chinese University of Hong Kong, Hong Kong. Professor Cao was an Associate Editor of the IEEE Transactions on Neural Networks, and Neurocomputing. He is an Associate Editor of the IEEE Transactions on Cybernetics, IEEE Transactions on Cognitive and Developmental Systems, Journal of the Franklin Institute, Mathematics and Computers in Simulation, Cognitive Neurodynamics, and Neural Networks. He is a Fellow of IEEE, a Member of the Academy of Europe, a Member of European Academy of Sciences and Arts and a Foreign Fellow of Pakistan Academy of Sciences. He has been named as Highly-Cited Researcher in Engineering,Computer Science, and Mathematics by Thomson Reuters/Clarivate Analytics. He received the National Innovation Award of China (2017).

Ahmed Alsaedi received his Ph.D. degree from Swansea University (UK) in 2002. He has a broad experience of research in applied mathematics. His fields of interest include dynamical systems, nonlinear analysis involving ordinary differential equations, fractional differential equations, boundary value problems, mathematical modeling, biomathematics, Newtonian and Non-Newtonian fluid mechanics. He has published several articles in peer-reviewed journals. He supervised several M.S/Ph.D students and executed many funded research projects. He is a reviewer of several international journals. He served as the chairman of the mathematics department at KAU and presently he is serving as director of the research program at KAU. Under his great leadership, this program is running quite successfully, and it has attracted a large number of highly rated researchers and distinguished professors from all over the world. He is also the head of NAAM international research group at KAU.

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Wei, R., Cao, J. & Alsaedi, A. Fixed-time Synchronization of Memristive Cohen-Grossberg Neural Networks with Impulsive Effects. Int. J. Control Autom. Syst. 16, 2214–2224 (2018). https://doi.org/10.1007/s12555-017-0788-5

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  • DOI: https://doi.org/10.1007/s12555-017-0788-5

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