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Particle filtering with alpha-stable distributions

Mihaylova, L. and Brasnett, P. and Achim, A. and Bull, D. and Canagarajah, N. (2005) Particle filtering with alpha-stable distributions. In: Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on :. , 381 - 386. ISBN 0-7803-9403-8

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    In this paper we introduce a novel sequential Monte Carlo technique, which is based on the family of symmetric alpha- stable (SAS) distributions. Sequential Bayesian estimation generally involves recursive estimation of filtering and predictive distributions of unobserved signals from their noisy measurements. In our proposed algorithm, the relevant density functions are approximated by particles drawn from stable distributions. We call this novel technique SAS particle filtering (SASPF). We assess the performance of the SASPF in comparison with the Gaussian Sum particle filter (GSPF) [1] and a standard (non-parametric) particle filter (PF). Results obtained using highly nonlinear models with simulated data show that the SASPF outperforms the GSPF and compares very favorably with the PF.

    Item Type: Contribution in Book/Report/Proceedings
    Additional Information: "©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
    Uncontrolled Keywords: alpha stable distributions ; particle filtering ; estimation ; nonlinear systems DCS-publications-id ; inproc-431 ; DCS-publications-credits ; dsp-fa ; DCS-publications-personnel-id ; 121
    Subjects: ?? qa75 ??
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 4367
    Deposited By: Dr L Mihaylov
    Deposited On: 10 Mar 2008 13:37
    Refereed?: No
    Published?: Published
    Last Modified: 18 Jul 2018 01:15
    Identification Number:

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