Additive Cellular Automata Augmented with Deep Learning for Pattern Reorganization

P Kiran Sree, SSSN Usha Devi N

Abstract


This article also a new approach to classify several problems based on the properties of Additive Cellular Automata. We use a state-transition 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.


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References


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