An exhaustive analysis of emergent behaviors in recurrent cellular computing systems with outer-totalistic cells

This paper introduces a set of systematic tools to identify and classify emergent behaviors in recurrent Cellular Neural Networks (CNN) emulating binary cellular automata (CA). Some relationships are established between the class of behavior and the structural complexity of a nonlinear neural cell implementing outer-totalistic local Boolean functions.