contributor author | S. Roy | |
contributor author | Chowdhury | |
contributor author | Roy | |
contributor author | R. M. | |
contributor author | Vasu | |
date accessioned | 2017-05-08T21:43:58Z | |
date available | 2017-05-08T21:43:58Z | |
date copyright | February 2013 | |
date issued | 2013 | |
identifier other | %28asce%29em%2E1943-7889%2E0000489.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/60962 | |
description abstract | A 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. | |
publisher | American Society of Civil Engineers | |
title | Variance-Reduced Particle Filters for Structural System Identification Problems | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 2 | |
journal title | Journal of Engineering Mechanics | |
identifier doi | 10.1061/(ASCE)EM.1943-7889.0000480 | |
tree | Journal of Engineering Mechanics:;2013:;Volume ( 139 ):;issue: 002 | |
contenttype | Fulltext | |