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Stability analysis of fractional order fuzzy cellular neural networks with leakage delay and time varying delays
Institution:1. Faculty of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 36199–95161, Iran;2. Institute of Engineering, Polytechnic of Porto, Department of Electrical Engineering, Rua Dr. António Bernardino de Almeida 431, 4249-015 Porto, Portugal;1. College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China;2. School of Mathematics, Southeast University, Nanjing 210096, China;3. Department of Mathematics, Harbin Institute of Technology at Weihai, Shandong 264209, China;1. College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China;2. School of Mathematics, Southeast University, Nanjing 210096, China;1. School of Artificial Intelligence and Automation, the Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Control Science and Engineering, Shandong University, Jinan 250061, China;3. School of Mathematical Sciences, Qufu Normal University, Qufu 273165, Shandong, China;1. Department of Mathematics, Thiruvalluvar University, Vellore 632 115, Tamilnadu, India;2. Department of Electrical and Electronics Engineering, NIET Great Noida, Uttrapradesh, India;3. Nonlinear Analysis and Applied Mathematics (NAAM)-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia
Abstract:In this paper we investigated the stability of fractional order fuzzy cellular neural networks with leakage delay and time varying delays. Based on Lyapunov theory and applying bounded techniques of fractional calculation, sufficient criterion are established to guarantee the stability. Hybrid feedback control is applied to derive the proposed results. Finally, numerical examples with simulation results are given to illustrate the effectiveness of the proposed method.
Keywords:Fractional order  Mittag-Leffler stability  Fuzzy cellular neural networks  Time varying delays
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