Pinning exponential synchronization for inertial coupled neural networks via adaptive aperiodically intermittent control under directed topology |
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| Institution: | 1. College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, PR China;2. School Mathematics and Statistics, Yili Normal University, YiNing 835000, PR China;1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China;2. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China;1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China;2. Institute of Complexity Science, Qingdao University, Qingdao 266071, China;3. College of Automation Engineering, Qingdao University of Technology, Qingdao 266555, China;1. College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China;2. School of Mathematics and Information Science, Henan Polytechnic University, Jiaozuo, 454000, Henan, P.R. China |
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| Abstract: | This article is mainly focused on investigating pinning exponential synchronization of inertial coupled neural networks (ICNNs) under different directed topologies. The traditional method of variable substitution is removed and replaced by non-reduced order method to investigate the dynamical behavior of second-order coupled system. Additionally, by constructing Lyapunov-Krasovskii functional and utilizing matrix decomposition theory as well as M-matrix theory, an adaptive aperiodically intermittent controller is introduced to derive several improved sufficient criteria based on linear matrix inequalities (LMIs). Finally, some examples with numerical simulation are exhibited to confirm the availability of the theoretical results. |
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