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We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV (www.arxiv.org) that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint
7/1998

Attractor switching by neural control of chaotic neurodynamics

Frank Pasemann and Nico Stollenwerk

Abstract

Chaotic attractors of discrete-time neural networks include infinitely many unstable periodic orbits, which can be stabilized by small parameter changes in a feedback control. Here we explore the control of unstable periodic orbits in a chaotic neural network with only two neurons. Analytically a local control algorithm is derived on the basis of least squares minimization of the future deviations between actual system states and the desired orbit. This delayed control allows a consistent neural implementation, i.e. the same types of neurons are used for chaotic and controlling modules. The control signal is realized with one layer of neurons, allowing selective switching between different stabilized periodic orbits. For chaotic modules with noise random switching between different periodic orbits is observed.

Received:
Feb 12, 1998
Published:
Feb 12, 1998

Related publications

inJournal
1998 Repository Open Access
Nico Stollenwerk and Frank Pasemann

Attractor switching by neural control of chaotic neurodynamics

In: Network : computation in neural systems, 9 (1998) 4, pp. 549-561