Variance-Reduced Particle Filters for Structural System Identification Problems
Data(s) |
2013
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Resumo |
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. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers. |
Formato |
application/pdf |
Identificador |
http://eprints.iisc.ernet.in/46467/1/jl_eng_mec_asc_139_2_210_2013.pdf Chowdhury, Roy S and Roy, D and Vasu, RM (2013) Variance-Reduced Particle Filters for Structural System Identification Problems. In: JOURNAL OF ENGINEERING MECHANICS-ASCE, 139 (2). pp. 210-218. |
Publicador |
ASCE-AMER SOC CIVIL ENGINEERS |
Relação |
http://dx.doi.org/10.1061/(ASCE)EM.1943-7889.0000480 http://eprints.iisc.ernet.in/46467/ |
Palavras-Chave | #Civil Engineering #Instrumentation and Applied Physics (Formally ISU) |
Tipo |
Journal Article PeerReviewed |