Identification of coupled map lattice models of stochastic spatio-temporal dynamics using wavelets

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 multiresolution 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 nonlinear spatio-temporal dynamics. Two examples are used to demonstrate the application of the proposed new approach.