Effective Computation of 2D Coupled Map Lattices Jacques Blanc-Talon
Abstract
	Approximate identification of coupled map lattices Êis considered. The local dynamics is split into a local function, expanded in Hermite's polynomial series, and a coupling one which is the convolution product of the neighborhoods by a kernel. The local function fits the data set (an image) while the convolution kernel of the coupling function is adjusted to fit a set of some selected patterns, gathering the so-called ``structural information''. The structural information to be considered is shown to be the connected set of the zero-crossings of the Laplacian of the input image Ê, which is computed by using Gauss kernels. A practical computation of a CML from stone patterns is shown.

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