Title :
Exponential stability of the steady state solution of Hopfield neural networks with reaction-diffusion terms under the L2 norm
Author :
Zhao, Xinquan ; Zhou, Lun ; Liao, Xiaoxin
Author_Institution :
Dept. of Autom. Control Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
Abstract :
In this paper, local asymptotic stability and global asymptotic stability of the steady state solutions of Hopfield neural networks with reaction-diffusion terms are investigated. Under the L2 norm, applying the differential inequality some sufficiency criterions for local exponential stability and global exponential stability of the steady state solution of system are established.
Keywords :
Hopfield neural nets; asymptotic stability; circuit stability; Hopfield neural networks; exponential stability; global asymptotic stability; reaction-diffusion terms; steady state solution; Asymptotic stability; Educational institutions; Equations; Hopfield neural networks; Intelligent networks; Lyapunov method; Neural networks; Roads; Stability criteria; Steady-state;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1202795
