Title :
Exponential Synchronization of Delayed Neural Networks With Discontinuous Activations
Author :
Xinsong Yang ; Jinde Cao
Author_Institution :
Dept. of Math., Chongqing Normal Univ., Chongqing, China
Abstract :
This paper investigates drive-response synchronization of a class of neural networks with time-varying delays and discontinuous activations. Discontinuous state feedback controller and adaptive controller are designed such that the considered model can realize exponential complete synchronization. Moreover, the convergence rate is explicitly estimated when state feedback control is utilized. The obtained results are also applicable to neural networks with continuous activations since they are a special case of neural networks with discontinuous activations. Results of this paper improve corresponding ones which only quasi-synchronization can be achieved for neural networks with discontinuous activations. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.
Keywords :
adaptive control; control system synthesis; delays; neurocontrollers; sampled data systems; state feedback; synchronisation; adaptive controller; continuous activations; convergence rate; delayed neural networks; discontinuous activations; discontinuous state feedback controller; drive-response synchronization; exponential complete synchronization; numerical simulations; quasisynchronization; time-varying delays; Adaptive control; Filippov solutions; discontinuous activations; exponential synchronization; neural networks; state feedback control;
Journal_Title :
Circuits and Systems I: Regular Papers, IEEE Transactions on
DOI :
10.1109/TCSI.2013.2244451