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Generalized sinc-Gaussian sampling involving derivatives

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Abstract

The generalized sampling expansion which uses samples from a bandlimited function f and its first r derivatives was first introduced by Linden and Abramson (Inform. Contr. 3, 26–31, 1960) and it was extended in different situations by some authors through the last fifty years. The use of the generalized sampling series in approximation theory is limited because of the slow convergence. In this paper, we derive a modification of a generalized sampling involving derivatives, which is studied by Shin (Commun. Korean Math. Soc. 17, 731–740, 2002), using a Gaussian multiplier. This modification is introduced for wider classes, the class of entire functions including unbounded functions on ℝ and the class of analytic functions in a strip. It highly improves the convergence rate of the generalized sampling which will be of exponential order. We will show that many known results included in Sampl. Theory Signal Image Process. 9, 199–221 (2007) and Numer. Funct. Anal. Optim. 36, 419–437 (2015) are special cases of our results. Numerical examples show a rightly good agreement with our theoretical analysis.

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Authors and Affiliations

  1. Department of Mathematics, College of Arts and Sciences, Najran University, Najran, Saudi Arabia

    R. M. Asharabi

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  1. R. M. Asharabi
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Asharabi, R.M. Generalized sinc-Gaussian sampling involving derivatives. Numer Algor 73, 1055–1072 (2016). https://doi.org/10.1007/s11075-016-0129-4

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  • DOI: https://doi.org/10.1007/s11075-016-0129-4

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