This paper introduces a new approach for the local reconstruction of coupled map lattice (CML) models of stochastic spatio-temporal dynamics from measured data. The nonlinear functionals describing the evolution of the spatio-temporal patterns are constructed using B-spline wavelet and scaling functions. This provides a multi-resolution approximation for the underlying spatio-temporal dynamics. An orthogonal least squares algorithm is used to determine significant terms from wavelet functions to form an accurate representation of the non-linear spatio-temporal dynamics. Two examples are used to demonstrate the application of the proposed new approach.
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