Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/588227
Title: A Robust Gaussian Approximate Fixed-Interval Smoother for Nonlinear Systems With Heavy-Tailed Process and Measurement Noises
Authors: Yulong Huang;Yonggang Zhang;Ning Li;Jonathon Chambers
subject: Student’s t distribution|Gaussian approximate smoother|heavy-tailed noise|variational Bayesian
Year: 2016
Publisher: IEEE
Abstract: In this letter, a robust Gaussian approximate (GA) fixed-interval smoother for nonlinear systems with heavy-tailed process and measurement noises is proposed. The process and measurement noises are modeled as stationary Student's t distributions, and the state trajectory and noise parameters are inferred approximately based on the variational Bayesian (VB) approach. Simulation results show the efficiency and superiority of the proposed smoother as compared with existing smoothers.
URI: http://localhost/handle/Hannan/167753
http://localhost/handle/Hannan/588227
ISSN: 1070-9908
1558-2361
volume: 23
issue: 4
Appears in Collections:2016

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Title: A Robust Gaussian Approximate Fixed-Interval Smoother for Nonlinear Systems With Heavy-Tailed Process and Measurement Noises
Authors: Yulong Huang;Yonggang Zhang;Ning Li;Jonathon Chambers
subject: Student’s t distribution|Gaussian approximate smoother|heavy-tailed noise|variational Bayesian
Year: 2016
Publisher: IEEE
Abstract: In this letter, a robust Gaussian approximate (GA) fixed-interval smoother for nonlinear systems with heavy-tailed process and measurement noises is proposed. The process and measurement noises are modeled as stationary Student's t distributions, and the state trajectory and noise parameters are inferred approximately based on the variational Bayesian (VB) approach. Simulation results show the efficiency and superiority of the proposed smoother as compared with existing smoothers.
URI: http://localhost/handle/Hannan/167753
http://localhost/handle/Hannan/588227
ISSN: 1070-9908
1558-2361
volume: 23
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7416166.pdf304.3 kBAdobe PDFThumbnail
Preview File
Title: A Robust Gaussian Approximate Fixed-Interval Smoother for Nonlinear Systems With Heavy-Tailed Process and Measurement Noises
Authors: Yulong Huang;Yonggang Zhang;Ning Li;Jonathon Chambers
subject: Student’s t distribution|Gaussian approximate smoother|heavy-tailed noise|variational Bayesian
Year: 2016
Publisher: IEEE
Abstract: In this letter, a robust Gaussian approximate (GA) fixed-interval smoother for nonlinear systems with heavy-tailed process and measurement noises is proposed. The process and measurement noises are modeled as stationary Student's t distributions, and the state trajectory and noise parameters are inferred approximately based on the variational Bayesian (VB) approach. Simulation results show the efficiency and superiority of the proposed smoother as compared with existing smoothers.
URI: http://localhost/handle/Hannan/167753
http://localhost/handle/Hannan/588227
ISSN: 1070-9908
1558-2361
volume: 23
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7416166.pdf304.3 kBAdobe PDFThumbnail
Preview File