Department of Automatic Control and Systems Engineering
Abstract
Extracting the rules from spatio-temporal patterns generated by the evolution of Cellular Automata (CA) usually produces a CA rule tablet without providing a clear understanding of the structure of the neighbourhood or the CA rule. In the present paper a new identification method based on using a modified orthogonal least squares or CA-OLS algorithm to detect the neighbourhood structure and the underlying polynomial form of the CA rules is proposed. The Quine-McClauskey method is then applied to extract minimum Boolean expressions from the polynomials. Spatio-temporal patterns produced by the evolution of one-, two-and higher-dimensional binary CA's are used to illustrate the new algorithm and simulation results show that the CA-OLS algorithm can quickly select both the correct neighbourhood structure and the corresponding rule
