Title :
Asymptotic stability of a class of generalized Hopfield neural networks with time delay and nonsymmetric interconnecting structure
Author :
Ji, Ce ; Zhang, Huaguang
Author_Institution :
Dept. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Since time delay and parameters uncertainty are inevitable, the asymptotic stability of the generalized Hopfield neural networks with time delay and nonsymmetric interconnecting structure is analyzed. The sufficient conditions for the asymptotic stability of equilibrium point are established by way of constructing a suitable Lyapunov functional and sector conditions. The simulation results are presented to prove the effectiveness of the conclusion.
Keywords :
Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; generalisation (artificial intelligence); uncertain systems; Lyapunov functional; asymptotic stability; generalized Hopfield neural networks; nonsymmetric interconnecting structure; parameter uncertainty; sufficient conditions; time delay; Asymptotic stability; Delay effects; Equations; Hopfield neural networks; Neural networks; Neurons; Stability analysis; Stability criteria; Sufficient conditions; Uncertain systems;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341935
