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contributor authorS. Roy
contributor authorChowdhury
contributor authorRoy
contributor authorR. M.
contributor authorVasu
date accessioned2017-05-08T21:43:58Z
date available2017-05-08T21:43:58Z
date copyrightFebruary 2013
date issued2013
identifier other%28asce%29em%2E1943-7889%2E0000489.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/60962
description abstractA few 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 the model parameters appears to be quite noticeable.
publisherAmerican Society of Civil Engineers
titleVariance-Reduced Particle Filters for Structural System Identification Problems
typeJournal Paper
journal volume139
journal issue2
journal titleJournal of Engineering Mechanics
identifier doi10.1061/(ASCE)EM.1943-7889.0000480
treeJournal of Engineering Mechanics:;2013:;Volume ( 139 ):;issue: 002
contenttypeFulltext


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