NON UNIFORM ADDITIVE NON UNIFORM CELLULAR AUTOMATA WITH DEEP LEARNING (ACADL) FOR PATTERN CLASSIFICATION

Abstract

This article depicts a new approach to classify several problems based on the properties of Additive Non uniform cellular automata. We use a statetransition which consists of a set of disjoint trees rooted at cyclic states of unit cycle length thus forming a natural classifier. The framework proposed is strengthened with genetic algorithm to find the desired local rule of the modeling as a global state function