Design of memory controllers for finite-time stabilization of delayed neural networks with uncertainty |
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| Authors: | Xiaoyu Zhang Xiaodi Li Jinde Cao Foued Miaadi |
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| Institution: | 1. School of Mathematics and Statistics, Shandong Normal University, Ji’nan\n250014, PR China;2. Department of Mathematics and Statistics, Memorial University of Newfoundland, St John’s A1C5S7, Canada;3. Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, Shandong Normal University, Jinan, PR China;4. School of Mathematics, Southeast University, Nanjing 210096, PR China;5. University of Carthage, Faculty of Sciences of Bizerta, Department of Mathematics, Research Units of Mathematics and Applications UR13ES47, Zarzouna, Bizerta 7021, Tunisia |
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| Abstract: | In this paper, we investigate the problem of finite-time stabilization of time-varying delayed neural networks with uncertainty. By employing the Lyapunov approach and linear matrix inequalities (LMIs), two different memory controllers are derived to achieve the finite-time stabilization of the addressed neural networks. Moreover, the upper bound of the setting-time for stabilization can be estimated via different Lyapunov functions. Our results improve and extend some recent works. Finally, the effectiveness and feasibility of the proposed controllers are demonstrated by numerical simulations. |
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| Keywords: | Corresponding author at: School of Mathematics and Statistics Shandong Normal University Ji’nan 250014 PR China |
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