Suppressing chaos in neural networks by noise

L. Molgedey, J. Schuchhardt, and H. G. Schuster
Phys. Rev. Lett. 69, 3717 – Published 28 December 1992
PDFExport Citation

Abstract

We study discrete parallel dynamics of a fully connected network of nonlinear elements interacting via long-range random asymmetric couplings under the influence of external noise. Using dynamical mean-field equations, which become exact in the thermodynamical limit, we calculate the activity and the maximal Lyapunov exponent of the network in dependence of a nonlinearity (gain) parameter and the noise intensity.

  • Received 20 July 1992

DOI:https://doi.org/10.1103/PhysRevLett.69.3717

©1992 American Physical Society

Authors & Affiliations

L. Molgedey, J. Schuchhardt, and H. G. Schuster

  • Institut für Theoretische Physik, Olshausenstrasse 40, D-2300 Kiel 1, Germany

References (Subscription Required)

Click to Expand
Issue

Vol. 69, Iss. 26 — 28 December 1992

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review Letters

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×