Neighbourhood detection and identification of spatio-temporal dynamical systems using a coarse-to-fine approach

Authors:
L. Z. Guo;S. S. Mei;S. A. Billings
Affiliations:
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK;Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK;Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
Venue:
International Journal of Systems Science
Year:
2007

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Abstract

A novel approach to the determination of the neighbourhood and the identification of spatio-temporal dynamical systems is investigated. It is shown that thresholding to convert the pattern to a binary pattern and then applying cellular automata (CA) neighbourhood detection methods can provide an initial estimate of the neighbourhood. A coupled map lattice model can then be identified using the CA detected neighbourhood as the initial conditions. This provides a coarse-to-fine approach for neighbourhood detection and identification of coupled map lattice models. Three examples are used to demonstrate the application of the new approach.