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Bayesian filtering for nonlinear state-space models in symmetric alpha-stable measurment noise

Author
Vila, J.; Fernandez, C.; Closas, P.; Fernandez, J.
Type of activity
Presentation of work at congresses
Name of edition
19th European Signal Processing Conference
Date of publication
2011
Presentation's date
2011-10-02
Book of congress proceedings
EURASIP 2011
First page
674
Last page
678
Repository
http://hdl.handle.net/2117/13816 Open in new window
URL
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569427609.pdf Open in new window
Abstract
Bayesian ltering appears in many signal processing problems,reason why it attracted the attention of many researchers to develop efficient algorithms, yet computationally a ordable. In many real systems, it is appropriate to consider α-stable noise distributions to model possible outliers or impulsive behavior in the measurements. In this paper, we consider a nonlinear state-space model with Gaussian process noise and symmetric α-stable measurement noise. To obtain a robust estimation framewo...
Citation
Vila, J. [et al.]. Bayesian filtering for nonlinear state-space models in symmetric alpha-stable measurment noise. A: European Signal Processing Conference. "2011 EUSIPCO - 19th European Signal Processing Conferenc". 2011, p. 674-678.
Group of research
SPCOM - Signal Processing and Communications Group

Participants

  • Vila Valls, Jordi  (author and speaker )
  • Fernandez Prades, Carles  (author and speaker )
  • Closas Gómez, Pau  (author and speaker )
  • Fernandez Rubio, Juan-antonio  (author and speaker )

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