Optimization Viewpoint on Kalman Smoothing with Applications to Robust and Sparse Estimation-Reference-Cited by-同舟云学术

Optimization Viewpoint on Kalman Smoothing with Applications to Robust and Sparse Estimation

Published:2013-09-13 Issue: Volume: Page:237-280
ISSN:1860-4862
Container-title:Compressed Sensing & Sparse Filtering
language:
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Author:

Aravkin Aleksandr Y.,Burke James V.,Pillonetto Gianluigi

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-38398-4_8

Reference49 articles.

1. Angelosante D, Roumeliotis SI, Giannakis GB (2009) Lasso-kalman smoother for tracking sparse signals. In: 2009 conference record of the 43rd Asilomar conference on signals, systems and computers, pp 181–185

2. Ansley CF, Kohn R (1982) A geometric derivation of the fixed interval smoothing algorithm. Biometrika 69:486–487

3. Aravkin A, Burke J, Pillonetto G (2011) Robust and trend-following Kalman smoothers using students t. In: International federation of automaic control (IFAC), 16th symposium of system identification, Oct 2011

4. Aravkin A, Burke J, Pillonetto G (2011) A statistical and computational theory for robust and sparse Kalman smoothing. In: International federation of automaic control (IFAC), 16th symposium of system identification, Oct 2011

5. Aravkin AY ( 2010) Robust methods with applications to Kalman smoothing and bundle adjustment. Ph.D. Thesis, University of Washington, Seattle, June 2010

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