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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5431
Title: Variance-reduced particle filters for structural system identification problems
Authors: Roy Chowdhury, Shubhankar
Roy D.
Vasu R.M.
Published in: Journal of Engineering Mechanics
Abstract: Afew variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of themodel parameters appears to be quite noticeable. ¬© 2013 American Society of Civil Engineers.
Citation: Journal of Engineering Mechanics(2013), 139(2): 210-218
URI: https://doi.org/10.1061/(ASCE)EM.1943-7889.0000480
http://repository.iitr.ac.in/handle/123456789/5431
Issue Date: 2013
Keywords: Directed bootstrap filter
Gain-based direction
Quasi-Monte Carlo simulations
Quasi-Newton direction
Structural system identification
ISSN: 7339399
Author Scopus IDs: 56818427600
7402439420
55663544800
Author Affiliations: Chowdhury, S.R., Computational Mechanics Laboratory, Dept. of Civil Engineering, Indian Institute of Science, Bangalore 560012, India
Roy, D., Computational Mechanics Laboratory, Dept. of Civil Engineering, Indian Institute of Science, Bangalore 560012,
Corresponding Author: Roy, D.; Computational Mechanics Laboratory, Dept. of Civil Engineering, Indian Institute of Science, Bangalore 560012, India; email: royd@civil.iisc.ernet.in
Appears in Collections:Journal Publications [CE]

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