Identification of the Neighbourhood and CA Rules from Spatio-temporal CA Patterns
Billings, S.A. and yANG, Y.X.
(1999)
Identification of the Neighbourhood and CA Rules from Spatio-temporal CA Patterns.
Research Report.
ACSE Research Report 751
.
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.
Metadata
Item Type:
Monograph
Authors/Creators:
Billings, S.A.
yANG, Y.X.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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