Title :
Synchronization control of discontinuous neural networks via approximation
Author :
Liu, Xiaoyang ; Cao, Jinde
Author_Institution :
Dept. of Math., Southeast Univ., Nanjing, China
Abstract :
In this paper, complete synchronization is considered for the delayed neural networks with discontinuous activation functions. Under the framework of Filippov solution and in the sense of generalized derivative, a novel control method is given by using approximation and linear matrix inequality (LMI) approach. Based on the detailed analysis of previous works, several criteria are derived to ensure the global asymptotical stability of the error system, and thus the response system synchronizes with the drive system. Simulation results are given to illustrate the theoretical results.
Keywords :
asymptotic stability; linear matrix inequalities; neurocontrollers; synchronisation; transfer functions; Filippov solution; LMI approach; delayed neural networks; discontinuous activation functions; discontinuous neural networks; error system; generalized derivative; global asymptotical stability; linear matrix inequality; response system; synchronization control; Chaos; Control systems; Electronic mail; Limit-cycles; Linear approximation; Linear matrix inequalities; Mathematics; Neural networks; Neurons; Nonlinear dynamical systems; Delayed neural networks; Discontinuous activation functions; Filippov solution; Generalized derivative; LMI approach; Synchronization;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498122