Title :
Robust adaptive convergence of uncertain CGNNs with mixed delays
Author :
Wang, Xiaohong ; Jiang, Minghui
Author_Institution :
Coll. of Sci., China Three Gorges Univ., Yichang
Abstract :
In this paper, the problem of robust adaptive convergence for uncertain Cohen-Grossberg neural networks(CGNNs) with mixed delays is investigated. Using the Lyapunov method and employing a novel lemma, some delay-independent conditions are derived to ensure the state variables of the discussed robust system to converge, globally, uniformly, exponentially to a ball in the state space with a pre-specified convergence rate. The effectiveness and usefulness of the results has been verified by a numerical example with graphical illustrations.
Keywords :
Lyapunov methods; adaptive control; convergence of numerical methods; delays; neurocontrollers; robust control; state-space methods; uncertain systems; Lyapunov method; mixed delay-independent condition; pre-specified convergence rate; robust adaptive convergence; state space variable; uncertain Cohen-Grossberg neural network; Associative memory; Convergence; Delay; Educational institutions; Eigenvalues and eigenfunctions; Lyapunov method; Neural networks; Robustness; State-space methods; Symmetric matrices;
Conference_Titel :
IT in Medicine and Education, 2008. ITME 2008. IEEE International Symposium on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-3616-3
Electronic_ISBN :
978-1-4244-2511-2
DOI :
10.1109/ITME.2008.4744039
