%A Zhao,Hui %A Liu,Aidi %A Wang,QingjiƩ %A Zheng,Mingwen %A Chen,Chuan %A Niu,Sijie %A Li,Lixiang %D 2021 %J Frontiers in Neurorobotics %C %F %G English %K Predefined-time synchronization,Coupled memristive neural networks,multi-links topology,Secure communication scheme,Lyapunov function %Q %R 10.3389/fnbot.2021.783809 %W %L %M %P %7 %8 2021-December-24 %9 Original Research %# %! Hui Zhao et al. Predefined-time synchronization of MCMNN %* %< %T Predefined-Time Stability/Synchronization of Coupled Memristive Neural Networks With Multi-Links and Application in Secure Communication %U https://www.frontiersin.org/articles/10.3389/fnbot.2021.783809 %V 15 %0 JOURNAL ARTICLE %@ 1662-5218 %X This paper explores the realization of a predefined-time synchronization problem for coupled memristive neural networks with multi-links (MCMNN) via nonlinear control. Several effective conditions are obtained to achieve the predefined-time synchronization of MCMNN based on the controller and Lyapunov function. Moreover, the settling time can be tunable based on a parameter designed by the controller, which is more flexible than fixed-time synchronization. Then based on the predefined-time stability criterion and the tunable settling time, we propose a secure communication scheme. This scheme can determine security of communication in the aspect of encrypting the plaintext signal with the participation of multi-links topology and coupled form. Meanwhile, the plaintext signals can be recovered well according to the given new predefined-time stability theorem. Finally, numerical simulations are given to verify the effectiveness of the obtained theoretical results and the feasibility of the secure communication scheme.