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Accession Number ADA581395
Title Dimensional Reduction for Filters of Nonlinear Systems with Time-Scale Separation.
Publication Date Mar 2013
Media Count 9p
Personal Author N. S. Namachchivaya R. B. Sowers
Abstract This project outlines a collection of problems which combine techniques of model reduction and filtering. The basis of this work is a collection of limit theories for stochastic processes which model dynamical systems with multiple time scales. These different time scales often allow one to find effective behaviors of the fast time scales. When the rates of change of different variables differ by orders of magnitude, efficient data assimilation can be accomplished by constructing nonlinear filtering equations for the coarse-grained signal. In particular, we study how scaling interacts with filtering via stochastic averaging. We combine our study of stochastic dimensional reduction and nonlinear filtering to provide a rigorous framework for identifying and simulating filters which are specifically adapted to the complexities of the underlying multi-scale dynamical system.
Keywords Dynamical systems
Homogenized hybrid particle filter
Mathematical filters
Nonlinear systems
Stochastic processes
Time scales

Source Agency Non Paid ADAS
NTIS Subject Category 72F - Statistical Analysis
72E - Operations Research
Corporate Author Illinois Univ. at Urbana-Champaign. Board of Trustees.
Document Type Technical report
Title Note Final rept. 15 Apr 2008-30 Nov 2011.
NTIS Issue Number 1325
Contract Number FA9550-08-1-0206

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