Sampling And Galerkin Reconstruction In Reproducing Kernel Spaces
Keywords
Finite rate of innovation; Galerkin reconstruction; Iterative approximation-projection algorithm; Oblique projection; Reproducing kernel space; Sampling
Abstract
In this paper, we introduce a fidelity measure depending on a given sampling scheme and we propose a Galerkin method in Banach space setting for signal reconstruction. We show that the proposed Galerkin method provides a quasi-optimal approximation, and the corresponding Galerkin equations could be solved by an iterative approximation-projection algorithm in a reproducing kernel subspace of Lp. Also we present detailed analysis and numerical simulations of the Galerkin method for reconstructing signals with finite rate of innovation.
Publication Date
9-1-2016
Publication Title
Applied and Computational Harmonic Analysis
Volume
41
Issue
2
Number of Pages
638-659
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.acha.2015.12.007
Copyright Status
Unknown
Socpus ID
84969931541 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84969931541
STARS Citation
Cheng, Cheng; Jiang, Yingchun; and Sun, Qiyu, "Sampling And Galerkin Reconstruction In Reproducing Kernel Spaces" (2016). Scopus Export 2015-2019. 3465.
https://stars.library.ucf.edu/scopus2015/3465