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Sampling signals with finite rate of innovation (2002)
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| Venue: | IEEE Transactions on Signal Processing |
| Citations: | 338 - 67 self |
BibTeX
@ARTICLE{Vetterli02samplingsignals,
author = {Martin Vetterli and Pina Marziliano and Thierry Blu},
title = {Sampling signals with finite rate of innovation},
journal = {IEEE Transactions on Signal Processing},
year = {2002},
volume = {50},
pages = {1417--1428}
}
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Abstract
Abstract—Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of innovation. Examples of signals with a finite rate of innovation include streams of Diracs (e.g., the Poisson process), nonuniform splines, and piecewise polynomials. Even though these signals are not bandlimited, we show that they can be sampled uniformly at (or above) the rate of innovation using an appropriate kernel and then be perfectly reconstructed. Thus, we prove sampling theorems for classes of signals and kernels that generalize the classic “bandlimited and sinc kernel ” case. In particular, we show how to sample and reconstruct periodic and finite-length streams of Diracs, nonuniform splines, and piecewise polynomials using sinc and Gaussian kernels. For infinite-length signals with finite local rate of innovation, we show local sampling and reconstruction based on spline kernels. The key in all constructions is to identify the innovative part of a signal (e.g., time instants and weights of Diracs) using an annihilating or locator filter: a device well known in spectral analysis and error-correction coding. This leads to standard computational procedures for solving the sampling problem, which we show through experimental results. Applications of these new sampling results can be found in signal processing, communications systems, and biological systems. Index Terms—Analog-to-digital conversion, annihilating filters, generalized sampling, nonbandlimited signals, nonuniform splines, piecewise polynomials, poisson processes, sampling. I.
Keyphrases
finite rate piecewise polynomial nonuniform spline poisson process sampling problem innovative part index term analog-to-digital conversion communication system spectral analysis finite number time instant finite local rate abstract consider class biological system signal processing infinite-length signal error-correction coding local sampling locator filter sinc kernel case spline kernel appropriate kernel gaussian kernel computational procedure experimental result finite-length stream
