Open Access

A Particle Filtering Approach to Change Detection for Nonlinear Systems

EURASIP Journal on Advances in Signal Processing20042004:326929

https://doi.org/10.1155/S1110865704408051

Received: 13 September 2003

Published: 7 November 2004

Abstract

We present a change detection method for nonlinear stochastic systems based on particle filtering. We assume that the parameters of the system before and after change are known. The statistic for this method is chosen in such a way that it can be calculated recursively while the computational complexity of the method remains constant with respect to time. We present simulation results that show the advantages of this method compared to linearization techniques.

Keywords

nonlinear filtering generalized likelihood ratio test CUSUM algorithm online change detection

Authors’ Affiliations

(1)
Electrical, Computer, and Systems Engineering Department, Rensselaer Polytechnic Institute
(2)
The Institute for Systems Research, University of Maryland

Copyright

© Azimi-Sadjadi and Krishnaprasad 2004

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.