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EURASIP Journal on Advances in Signal Processing
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A Particle Filtering Approach to Change Detection for Nonlinear Systems

EURASIP Journal on Advances in Signal Processing volume 2004, Article number: 326929 (2004) Cite this article

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.

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Authors and Affiliations

  1. Electrical, Computer, and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, 12180-3590, USA

    Babak Azimi-Sadjadi & P. S. Krishnaprasad

  2. The Institute for Systems Research, University of Maryland, College Park, MD, 20742, USA

    Babak Azimi-Sadjadi

Authors
  1. Babak Azimi-Sadjadi
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  2. P. S. Krishnaprasad
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Correspondence to Babak Azimi-Sadjadi.

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Azimi-Sadjadi, B., Krishnaprasad, P.S. A Particle Filtering Approach to Change Detection for Nonlinear Systems. EURASIP J. Adv. Signal Process. 2004, 326929 (2004). https://doi.org/10.1155/S1110865704408051

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  • DOI: https://doi.org/10.1155/S1110865704408051

Keywords

  • nonlinear filtering
  • generalized likelihood ratio test
  • CUSUM algorithm
  • online change detection