Spatiotemporal chaos in one-and two-dimensional coupled map lattices
Proceedings of the eighth annual international conference of the Center for Nonlinear Studies on Advances in fluid turbulence
An introduction to wavelets
The changing nature of network traffic: scaling phenomena
ACM SIGCOMM Computer Communication Review
Identification of coupled map lattice models for spatio-temporal patterns using wavelets
International Journal of Systems Science
Multiscale Modeling: A Bayesian Perspective
Multiscale Modeling: A Bayesian Perspective
Multiscale finite impulse response modeling
Engineering Applications of Artificial Intelligence
Identification of finite dimensional models of infinite dimensional dynamical systems
Automatica (Journal of IFAC)
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In this article, a new algorithm for the multiscale identification of spatio-temporal dynamical systems is derived. It is shown that the input and output observations can be represented in a multiscale manner based on a wavelet multiresolution analysis. The system dynamics at some specific scale of interest can then be identified using an orthogonal forward least-squares algorithm. This model can then be converted between different scales to produce predictions of the system outputs at different scales. The method can be applied to both multiscale and conventional spatio-temporal dynamical systems. For multiscale systems, the method can generate a parsimonious and effective model at a coarser scale while considering the effects from finer scales. Additionally, the proposed method can be used to improve the performance of the identification when the measurements are noisy. Numerical examples are provided to demonstrate the application of the proposed new approach.