A discrete firing event analysis of the adaptive cluster expansion network

Abstract

This paper describes how a hierarchical network for encoding sensor data (the adaptive cluster expansion network) can be constructed by linking together a number of elementary modules, each of which is a simple two-layer encoder/decoder network. To achieve this goal, a Bayesian analysis is applied to the discrete neural firing events that occur within each layer of the network.* This paper was presented at the Workshop on Information Theory and the Brain, held at the University of Stirling, UK, on 4–5 September 1995.