Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.acha.2010.11.007
Title: Approximation of frame based missing data recovery
Authors: Cai, J.-F.
Shen, Z. 
Ye, G.-B.
Keywords: 1 minimization
Covering number
Error estimation
Framelet
Missing data recovery
Uniform law of large numbers
Issue Date: Sep-2011
Citation: Cai, J.-F., Shen, Z., Ye, G.-B. (2011-09). Approximation of frame based missing data recovery. Applied and Computational Harmonic Analysis 31 (2) : 185-204. ScholarBank@NUS Repository. https://doi.org/10.1016/j.acha.2010.11.007
Abstract: Recovering missing data from its partial samples is a fundamental problem in mathematics and it has wide range of applications in image and signal processing. While many such algorithms have been developed recently, there are very few papers available on their error estimations. This paper is to analyze the error of a frame based data recovery approach from random samples. In particular, we estimate the error between the underlying original data and the approximate solution that interpolates (or approximates with an error bound depending on the noise level) the given data that has the minimal 1 norm of the canonical frame coefficients among all the possible solutions. © 2010 Elsevier Inc.
Source Title: Applied and Computational Harmonic Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/102876
ISSN: 10635203
DOI: 10.1016/j.acha.2010.11.007
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