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Exponential synchronization of Markovian jumping chaotic neural networks with sampled-data and saturating actuators
Institution:1. Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China;2. School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China;3. Department of Mathematics, Huzhou University, Huzhou 313000, China;4. Department of Mathematics, Yangzhou University, Yangzhou 225002, China;5. Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia;1. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, PR China;2. State Key Laboratory of Synthetical Automation of Process Industries, Northeastern University, Shenyang, Liaoning 110819, PR China;1. Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China;2. Department of Mathematics, Yangzhou University, Yangzhou 225002, China;3. Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Abstract:This paper deals with the problem of exponential synchronization of Markovian jumping chaotic neural networks with saturating actuators using a sampled-data controller. By constructing a proper Lyapunov–Krasovskii functional (LKF) with triple integral terms, and employing Jensen’s inequality, some new sufficient conditions for the exponential synchronization of considered chaotic neural networks are derived in terms of linear matrix inequalities (LMIs). The obtained LMIs can be easily solved by any of the available software. Finally, the numerical examples are provided to demonstrate the effectiveness of our theoretical results.
Keywords:Saturating actuator  Exponential synchronization  Markovian jumping neural network  Chaotic system  Sampled-data  Linear matrix inequality
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