Finite-Time Synchronization of Coupled Memrisive Neural Network via Robust Control
作者： Hui Zhao , Mingwen Zheng
DOI: 10.1109/ACCESS.2019.2896935
关键词: Lyapunov function 、 Memristor 、 Artificial neural network 、 Property (programming) 、 Synchronization (computer science) 、 Synapse 、 Interval (mathematics) 、 Scale (ratio) 、 Computer science 、 Control theory 、 Robust control
摘要: In this paper, the synchronization of drive-response coupled memristive neural networks (CMNNs) and CMNN with multi-links is investigated. The memristors show memory characteristics, low energy consumption, nanometer scale so that can more truly simulate working mechanism brain networks. classic treatment method no longer being applied because parameter-dependent property in CMNN. new approach proposed transformed into a class interval parameters under framework Filippov solution. This overcame problem mismatched be less conservative than those existing methods. Sufficient criteria are derived to guarantee based on concept Lyapunov function. Finally, effectiveness theories validated numerical experiments.
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