Title :
Robustness analysis of Hopfield and modified Hopfield neural networks in time domain
Author :
Shen, Jie ; Balakrishnan, S.N.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Missouri Univ., Rolla, MO, USA
Abstract :
A variant of the Hopfield network, called the modified Hopfield network is formulated. This network which consists of two mutually recurrent networks has more free parameters than the well-known Hopfield network. Stability analysis of this network is presented. The analysis is carried out in the time domain with an application of the Lyapunov method and robust control Lyapunov function. The current flow in the network is treated as a `control´. This `controller´ is shown to guarantee `a practically stabilizing control´. Analysis of the Hopfield network is also included for completion
Keywords :
Hopfield neural nets; Lyapunov methods; neurocontrollers; robust control; time-domain analysis; Lyapunov method; modified Hopfield neural networks; mutually recurrent networks; practically stabilizing control; robust control Lyapunov function; robustness analysis; time domain; Artificial neural networks; Control systems; Hopfield neural networks; Intelligent networks; Lyapunov method; Robust control; Robust stability; Robustness; Stability analysis; Time domain analysis;
Conference_Titel :
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-4394-8
DOI :
10.1109/CDC.1998.760835
