Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments

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Nemeth, C., Fearnhead, P. and Mihaylova, L. (2013) Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments. IEEE Transactions on Signal Processing, 62 (5). 1245 - 1255. ISSN 1053-587X

Abstract

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Authors/Creators:
  • Nemeth, C.
  • Fearnhead, P.
  • Mihaylova, L.
Copyright, Publisher and Additional Information: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Sequential Monte Carlo methods; joint state and parameter estimation; nonlin ear systems; particle learning; tracking maneuvering targets
Dates:
  • Published: 23 December 2013
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 12 Nov 2015 16:55
Last Modified: 04 Nov 2016 01:31
Published Version: http://dx.doi.org/10.1109/TSP.2013.2296278
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TSP.2013.2296278
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