Superimposed event detection by sequential Monte Carlo methods

Date
2007
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Source Title
Proceedings of the 15th Signal Processing and Communications Applications, IEEE 2007
Print ISSN
2165-0608
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Publisher
IEEE
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Language
Turkish
Type
Conference Paper
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Abstract

In this paper, we consider the detection of rare events by applying particle filtering. We model the rare event as an AR signal superposed on a background signal. The activation and deactivation times of the AR-signal are unknown. We solve the online detection problem of this superpositional rare event by extending the state space dimension by one. The additional parameter of the state represents the AR-signal, which is zero when deactivated. Numerical experiments demonstrate the effectiveness of our approach.

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Keywords
Argon, Management science, Mathematical models, Signal filtering and prediction, Signal processing, State space methods, Event detection, Numerical experiments, On-line detection, Particle Filtering, Rare events, Sequential Monte Carlo methods, State spaces, Monte Carlo methods
Citation
Published Version (Please cite this version)