Nonsmooth Finite-Time Synchronization of Switched Coupled Neural Networks

• Published in: IEEE transactions on cybernetics Vol. 46; no. 10; pp. 2360 - 2371
• Main Authors: Liu, Xiaoyang, Cao, Jinde, Yu, Wenwu, Song, Qiang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-10-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer Simulation; Convergence; Couplings; Discontinuous activations; finite-time synchronization (FTS); Neural networks; Neural Networks (Computer); Nonlinear Dynamics; Stability analysis; switched coupling; Switches; Synchronization
• ISSN: 2168-2267; 2168-2275
• DOI: 10.1109/TCYB.2015.2477366

This paper is concerned with the finite-time synchronization (FTS) issue of switched coupled neural networks with discontinuous or continuous activations. Based on the framework of nonsmooth analysis, some discontinuous or continuous controllers are designed to force the coupled networks to synchronize to an isolated neural network. Some sufficient conditions are derived to ensure the FTS by utilizing the well-known finite-time stability theorem for nonlinear systems. Compared with the previous literatures, such synchronization objective will be realized when the activations and the controllers are both discontinuous. The obtained results in this paper include and extend the earlier works on the synchronization issue of coupled networks with Lipschitz continuous conditions. Moreover, an upper bound of the settling time for synchronization is estimated. Finally, numerical simulations are given to demonstrate the effectiveness of the theoretical results.