Finite-Time Synchronization of Memristive Neural Networks Modeling in Terms of Voltage-Flux-Time
Leimin Wang, Yonghuan Wang, 李岩 Li Yan
Abstract
In this brief, the finite-time synchronization problem of delayed memristive neural networks (MNNs) is addressed by adopting a flux-controlled memristor model. First, based on the presented memristor model, the MNNs behave as a class of continuous systems with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2^{2n^{2}+n}$ </tex-math></inline-formula> variables. Then, the finite-time controllers are proposed to synchronize the voltage and flux states between the drive and response MNNs, respectively. Based on the inequality techniques and the Lyapunov method, new synchronization criteria for delayed MNNs are derived. Finally, the results are verified by numerical simulations.