PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

At the Edge of Chaos: Real-time Computations and self-organized Criticality in Recurrent Neural Networks
Thomas Natschlaeger, Nils Bertschinger and Robert Legenstein
In: NIPS 2004, 13-15 Dec 2004, Vancouver, Canada.

Abstract

In this paper we analyze the relationship between the computational capabilities of randomly connected networks of threshold gates in the timeseries domain and their dynamical properties. In particular we propose a complexity measure which we find to assume its highest values near the edge of chaos, i.e. the transition from ordered to chaotic dynamics. Furthermore we show that the proposed complexity measure predicts the computational capabilities very well: only near the edge of chaos are such networks able to perform complex computations on time series. Additionally a simple synaptic scaling rule for self-organized criticality is presented and analyzed.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Theory & Algorithms
ID Code:898
Deposited By:Robert Legenstein
Deposited On:06 January 2005