Open Access
December 2013 Dimensional reduction in nonlinear filtering: A homogenization approach
Peter Imkeller, N. Sri Namachchivaya, Nicolas Perkowski, Hoong C. Yeong
Ann. Appl. Probab. 23(6): 2290-2326 (December 2013). DOI: 10.1214/12-AAP901

Abstract

We propose a homogenized filter for multiscale signals, which allows us to reduce the dimension of the system. We prove that the nonlinear filter converges to our homogenized filter with rate $\sqrt{\varepsilon}$. This is achieved by a suitable asymptotic expansion of the dual of the Zakai equation, and by probabilistically representing the correction terms with the help of BDSDEs.

Citation

Download Citation

Peter Imkeller. N. Sri Namachchivaya. Nicolas Perkowski. Hoong C. Yeong. "Dimensional reduction in nonlinear filtering: A homogenization approach." Ann. Appl. Probab. 23 (6) 2290 - 2326, December 2013. https://doi.org/10.1214/12-AAP901

Information

Published: December 2013
First available in Project Euclid: 22 October 2013

zbMATH: 1288.60049
MathSciNet: MR3127936
Digital Object Identifier: 10.1214/12-AAP901

Subjects:
Primary: 35B27 , 60G35 , 60H15 , 60H35

Keywords: asymptotic expansion , BDSDE , dimensional reduction , Homogenization‎ , Nonlinear filtering , particle filtering , SPDE

Rights: Copyright © 2013 Institute of Mathematical Statistics

Vol.23 • No. 6 • December 2013
Back to Top