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

Volume

1

fYear

1998

fDate

1998

Firstpage

1046

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

Conference_Location

Tampa, FL

ISSN

0191-2216

Print_ISBN

0-7803-4394-8

Type

conf

DOI

10.1109/CDC.1998.760835

Filename

760835