Reconstructing Signals with Finite Rate of Innovation from Noisy Samples

被引：0
作者：
Ning Bi
M. Zuhair Nashed
Qiyu Sun
机构：
[1] Sun Yat-Sen University,Department of Scientific Computing and Computer Applications
[2] University of Central Florida,Department of Mathematics
来源：
Acta Applicandae Mathematicae | 2009年 / 107卷
关键词：
Sampling; Signals with finite rate of innovation; Regularized least squares; Mean squared error; Wiener filter;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：339 / 372
页数：33
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