Novelty based feedback regulation in artificial neural networks

• Authors: A. Rychwalska , P. Jablonski , M. Zochowski , A. Nowak
• Languages of publication: EN

Abstracts

EN

In this paper we present a theoretical framework for novelty based feedback regulation in artificial neural networks. Novelty is assessed on the basis of monitoring the coherence of network dynamics. The result of novelty detection is dynamically coupled to parameters that control the dynamics of the recognition process. The paper presents a new measure of novelty detection - the strength of the local field - and presents new simulation results concerning novelty detection. It also integrates previously published models and simulation results into a general dynamical model of feedback regulation.

Keywords

EN

COHERENCE; FEEDBACK; NEURAL NETWORK; NOVELTY; REGULATION

Discipline

• EXPERIMENTAL_BIOLOGY_&_MEDICINE: EXPERIMENTAL BIOLOGY & MEDICINE

• Journal: Acta Neurobiologiae Experimentalis
• Year: 2005
• Volume: 65
• Issue: 3
• Pages: 453-463

Contributors

author

A. Rychwalska

author

P. Jablonski

author

M. Zochowski

author

A. Nowak

• Document Type: ARTICLE
• Publication order reference: Andrzej Nowak, Warsaw School for Social Psychology, 19/31 Chodakowska St., 03-815 Warsaw, Poland