Title
Sampling Moments and Reconstructing Signals of Finite Rate of Innovation: Shannon Meets Strang–Fix
Abstract
Consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, nonuniform splines or piecewise polynomials, and call the number of degrees of freedom per unit of time the rate of innovation. Classical sampling theory does not enable a perfect reconstruction of such signals since they are not bandlimited. Recently, it was shown that, by using an adequate sampling kernel and a sampling rate greater or equal to the rate of innovation, it is possible to reconstruct such signals uniquely . These sampling schemes, however, use kernels with infinite support, and this leads to complex and potentially unstable reconstruction algorithms. In this paper, we show that many signals with a finite rate of innovation can be sampled and perfectly reconstructed using physically realizable kernels of compact support and a local reconstruction algorithm. The class of kernels that we can use is very rich and includes functions satisfying Strang-Fix conditions, exponential splines and functions with rational Fourier transform. This last class of kernels is quite general and includes, for instance, any linear electric circuit. We, thus, show with an example how to estimate a signal of finite rate of innovation at the output of an RC circuit. The case of noisy measurements is also analyzed, and we present a novel algorithm that reduces the effect of noise by oversampling
Year
DOI
Venue
2007
10.1109/TSP.2006.890907
IEEE Transactions on Signal Processing
Keywords
Field
DocType
Fourier transforms,RC circuits,signal reconstruction,signal sampling,splines (mathematics),RC circuit,Strang-Fix conditions,exponential splines,rational Fourier transform,sampling moments,signals reconstruction,unstable reconstruction algorithms,Analog-to-digital conversion,annihilating filter method,multiresolution approximations,sampling methods,splines,wavelets
Mathematical optimization,Oversampling,Polynomial,Bandlimiting,Sampling (signal processing),Reconstruction algorithm,Sampling (statistics),Piecewise,Signal reconstruction,Mathematics
Journal
Volume
Issue
ISSN
55
5
1053-587X
Citations 
PageRank 
References 
154
8.35
22
Authors
3
Search Limit
100154
Name
Order
Citations
PageRank
Dragotti, P.L.151239.29
Martin Vetterli2139262397.68
T Blu32574259.70