1986
DOI: 10.1109/tit.1986.1057205
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Extrapolating a band-limited function from its samples taken in a finite interval

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Cited by 39 publications
(41 citation statements)
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(11 reference statements)
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“…Then the mathematical problem is to find conditions under which f can be reconstructed completely from its samples f (x n ). This problem is almost completely understood thanks to the work of Duffin-Schaeffer, Beurling, Malliavin, Landau, Pavlov and others [5,2,3,12,13,14,15,17]. Their work has provided deep insights into sets of uniqueness, Riesz bases, and sets of stable sampling.…”
Section: Karlheinz Gröchenigmentioning
confidence: 99%
“…Then the mathematical problem is to find conditions under which f can be reconstructed completely from its samples f (x n ). This problem is almost completely understood thanks to the work of Duffin-Schaeffer, Beurling, Malliavin, Landau, Pavlov and others [5,2,3,12,13,14,15,17]. Their work has provided deep insights into sets of uniqueness, Riesz bases, and sets of stable sampling.…”
Section: Karlheinz Gröchenigmentioning
confidence: 99%
“…Accordingly, we can apply to it all results known for band-limited functions, in particular, the noteworthy property that these functions are analytical, i.e., such that their exact knowledge in a finitelength interval allows, in principle, their extrapolation over the entire domain of definition, having infinite extension [4][5][6][7][8][9], thus potentially prospecting the achievement of unlimited angular resolution. As extensively discussed in these references, however, the implementation aspects, such as the need to sample the field by means of a sensor array, with consequent loss of information due to the finiteness of the spatial sampling frequency, and the errors inherent in the analog-to-digital conversion and in the array implementation, along with other limiting factors, make the above extrapolation process reliable only within a limited range in the vicinity of the array.…”
Section: Introductionmentioning
confidence: 99%
“…In the literature, the mentioned techniques have been addressed with reference to different categories of problems. On the one hand, super-resolution algorithms have been studied extensively in the past in conjunction with ingenious extrapolation schemes to improve the discrimination capability of specific instrumentation, such as optical sensors or spectrum analyzers, in response to one-or two-dimensional band-limited signals observed in truncated intervals [4][5][6][7][8][9]. In these references the interest of researchers is mainly focused on the extrapolation schemes and the relevant performance limits, with no reference to their possible applications to beamforming issues.…”
Section: Introductionmentioning
confidence: 99%
“…As well-known, this is an ill-posed problem widely studied in literature with reference to the case of bandlimited signals which are known only in a finite time interval [12][13][14][15][16][17][18][19][20][21].…”
Section: Introductionmentioning
confidence: 99%
“…As explicitly stated in [21], when the samples are error affected, an accurate extrapolation of the signal is possible for at most a bounded distance beyond the observation interval. Accordingly, since physical measurements can never be perfect, this implies that only few samples external to the observation interval can be reliably estimated.…”
Section: Introductionmentioning
confidence: 99%