Open Access

A Particle Filtering Approach to Change Detection for Nonlinear Systems

EURASIP Journal on Advances in Signal Processing20042004:326929

Received: 13 September 2003

Published: 7 November 2004


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.


nonlinear filteringgeneralized likelihood ratio testCUSUM algorithmonline change detection

Authors’ Affiliations

Electrical, Computer, and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, USA
The Institute for Systems Research, University of Maryland, College Park, USA


© 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.