Identification of Excitable Media Using Cellular Automata Models

Excitable media represent an important class of spatio-temporal systems which can be studied using cellular automata models. In the present study examples of excitable media behavior generated using simple cellular automata models are introduced. A mutual information algorithm is then derived to determine the neighborhood, the excitation threshold, and the number of excitation states. Based on this information two methods of identifying the rule which describes the excitable media pattern using a multimodel and a polynomial model are introduced. The results are illustrated using simulated examples and real data from a Belousov–Zhabotinskii experiment.

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