Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays

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Abstract
In this paper, adaptive synchronization of memristor-based neural networks (MNNs) with time-varying delays is investigated. The dynamical analysis here employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. Sufficient conditions for the global synchronization of MNNs are established with a general adaptive controller. The update gain of the controller can be adjusted to control the synchronization speed. The obtained results complement and improve the previously known results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results.
Funding Information
  • Key Program of National Natural Science Foundation of China (61134012)
  • National Science Foundation of China (11271146)
  • Science and Technology Program, Wuhan, China (2013010501010117)
  • Doctoral Program of Higher Education of China (20130142130012)

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