Title :
Synchronization for competitive neural networks by output feedback and impulsive control
Author :
Haibo Gu ; Haibo Lu
Author_Institution :
Coll. of Math. Sci., Xinjiang Normal Univ., Urumqi, China
Abstract :
In this paper, a linear static output feedback impulsive control law is designed to achieve globally exponential synchronization of coupled delayed competitive neural networks with different time scales. By using Lyapunov functional method and mathematical induction method, some sufficient conditions for globally exponential synchronization of coupled neural networks via output feedback impulsive control are established. With the help of LMI solvers, a linear output feedback impulsive controllers can be obtained easily. An example with numerical simulation is given to demonstrate the effectiveness of the theory results.
Keywords :
Lyapunov methods; feedback; linear matrix inequalities; neurocontrollers; numerical analysis; synchronisation; LMI solvers; Lyapunov functional method; competitive neural network synchronization; coupled delayed competitive neural networks; coupled neural networks; globally exponential synchronization; linear output feedback impulsive controllers; linear static output feedback impulsive control law; mathematical induction method; numerical simulation; Biological neural networks; Chaotic communication; Neurons; Output feedback; Stability analysis; Synchronization; Competitive neural networks; Impulsive control; LMI method; Synchronization;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561298