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2019
DOI: 10.1016/j.jat.2018.09.009
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Relevant sampling in finitely generated shift-invariant spaces

Abstract: We consider random sampling in finitely generated shift-invariant spaces V (Φ) ⊂ L 2 (R n ) generated by a vector Φ = (ϕ 1 , . . . , ϕ r ) ∈ L 2 (R n ) r . Following the approach introduced by Bass and Gröchenig, we consider certain relatively compact subsets V R,δ (Φ) of such a space, defined in terms of a concentration inequality with respect to a cube with side lengths R. Under very mild assumptions on the generators, we show that for R sufficiently large, taking O(R n log(R n 2 /α ′ )) many random samples … Show more

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Cited by 41 publications
(35 citation statements)
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“…Randomized algorithms in a context of continuous frames were presented in the past. Relevant sampling is a line of work in which integral transforms are randomly discretized [5,24,42,49]. While the goal in our approach is to approximate the continuous frame with a quadrature sum, the goal in relevant sampling is to sample discrete frames from continuous frames.…”
Section: Randomized Quadrature Approximations Of Continuous Framesmentioning
confidence: 99%
See 1 more Smart Citation
“…Randomized algorithms in a context of continuous frames were presented in the past. Relevant sampling is a line of work in which integral transforms are randomly discretized [5,24,42,49]. While the goal in our approach is to approximate the continuous frame with a quadrature sum, the goal in relevant sampling is to sample discrete frames from continuous frames.…”
Section: Randomized Quadrature Approximations Of Continuous Framesmentioning
confidence: 99%
“…Definition24 Let H be a Hilbert space that we call the signal space. A class of signals R ⊂ H is a (possibly non-linear) subset of H. A sequence of discretizations of R is a sequence of (generally non-linear) subspaces {V M ⊂ H} ∞ M=1 that satisfies the following condition: for every s ∈ R there is a sequence {s…”
mentioning
confidence: 99%
“…They obtained the probabilistic sampling inequality for band-limited functions on R in [3] and the same for band-limited functions on R d in [4]. Random sampling in shift-invariant spaces was studied in [26,24,9]. Yang and Tao in [25] studied random sampling and gave an approximation model for signals having bounded derivatives.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, random sampling has become a rather active area of research, due to its simplicity, flexibility and effectiveness, researchers investigate random sampling for different function spaces [1,2,6,7,18]. Besides, centered discrepancy of random sampling and Latin hypercube sampling are investigated in [19].…”
Section: Introductionmentioning
confidence: 99%