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Structural organization of a Boolean cellular automata

This paper deals with the notion of structural organization of Boolean cellular automata as an evolutive concept driving the cellular state space grouping, as nearly as possible, of the desired final distribution. In this respect, there is assumed the introduction of a set of specific categories as the union of structural state combinations. The transition rule is applied to each neighborhood if the structural organizational degree, estimated as the chance of evolution toward the desired category, overtakes an empirical threshold. The convergence of the cellular automata organizational process is discussed by studying the Lyapunov function of the synchronous iteration trajectory which drives to the stable configuration. This function is based on the informational entropy conveyed by each neighborhood, as a performance criterion. The category weights are evaluated, i.e., the strengths of the encouragement character of certain categories during the evolutionary process. Finally, some possible applications in the field of image processing are listed.