Multiresolution stochastic models for the efficient solution of large-scale space-time estimation problems

SOLUTION OF LARGE-SCALE SPACE-TIME ESTIMATION PROBLEMS Terrence T. Ho, Paul W. Fieguth, Alan S. Willsky Laboratory for Information and Decision Systems Massachusetts Institute of Technology, Cambridge, MA 02139 ABSTRACT The successful application of a recently developed treebased multiscale estimation framework [1] to large-scale static estimation problems has proven the statistical exibility and the computational e ciency of the framework. However, the estimation of processes evolving in time remains a considerable challenge. In this paper, we address this challenge by investigating multiscale models for the steady-state estimation of dynamic systems. In particular, we build such models for 1-D and 2-D heat di usion processes, making use of a canonical correlations realization technique.