Robust synchronization of discontinuous Cohen–Grossberg neural networks: Pinning control approach |
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Authors: | Dongshu Wang Lihong Huang |
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Institution: | 1. Fujian Province University Key Laboratory of Computation Science, School of Mathematical Sciences, Huaqiao University, 362021, Quanzhou, Fujian, PR China;2. School of Mathematics and Statistics, Central South University, Changsha, Hunan 410083, PR China;3. Changsha University of Science and Technology, Changsha, Hunan 410014, PR China |
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Abstract: | In this issue, the robust synchronization for a class of uncertain Cohen–Grossberg neural networks is studied, in which neuron activations are modelled by discontinuous functions(or piecewise continuous functions). Pinning state-feedback and adaptive controllers are designed to achieve global robust exponential synchronization and global robust asymptotical synchronization of drive-response-based discontinuous Cohen–Grossberg neural networks. By applying the theory of non-smooth analysis theory and the method of generalized Lyapunov functional, some criteria are given to show that the coupled discontinuous Cohen–Grossberg neural networks with parameter uncertainties can realized global robust synchronization. Some examples and numerical simulations are also shown to verify the validity of the proposed results. |
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Keywords: | Corresponding author at: Fujian Province University Key Laboratory of Computation Science School of Mathematical Sciences Huaqiao University Quanzhou Fujian 362021 PR China |
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