Title
Reconstructing Signals with Finite Rate of Innovation from Noisy Samples
Abbreviated Journal Title
Acta Appl. Math.
Keywords
Sampling; Signals with finite rate of innovation; Regularized least; squares; Mean squared error; Wiener filter; SHIFT-INVARIANT SPACES; SHANNON; REGULARIZATION; Mathematics, Applied
Abstract
A signal is said to have finite rate of innovation if it has a finite number of degrees of freedom per unit of time. Reconstructing signals with finite rate of innovation from their exact average samples has been studied in Sun (SIAM J. Math. Anal. 38, 1389-1422, 2006). In this paper, we consider the problem of reconstructing signals with finite rate of innovation from their average samples in the presence of deterministic and random noise. We develop an adaptive Tikhonov regularization approach to this reconstruction problem. Our simulation results demonstrate that our adaptive approach is robust against noise, is almost consistent in various sampling processes, and is also locally implementable.
Journal Title
Acta Applicandae Mathematicae
Volume
107
Issue/Number
1-3
Publication Date
1-1-2009
Document Type
Article; Proceedings Paper
Language
English
First Page
339
Last Page
372
WOS Identifier
ISSN
0167-8019
Recommended Citation
"Reconstructing Signals with Finite Rate of Innovation from Noisy Samples" (2009). Faculty Bibliography 2000s. 1355.
https://stars.library.ucf.edu/facultybib2000/1355
Comments
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