A cellular system for pattern recognition using associative neural networks

Abstract

A cellular system for pattern recognition is presented. The cells are placed in a two dimensional array and they are capable of performing basic symbolic processing and exchanging messages about their state. Following a cellular automata like operation the aim of the system is to transform an initial symbolic description of a pattern to a correspondent object level representation. To this end, a hierarchical approach for the description of the structure of the patterns is followed. The underlying processing engine of the system is the AURA model of associative memory. The system is endowed with a learning mechanism utilizing the distributed nature of the architecture. A dedicated hardware platform is also available.