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Mellin transform

About: Mellin transform is a research topic. Over the lifetime, 3272 publications have been published within this topic receiving 63220 citations.


Papers
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Book
08 Sep 2011

1,487 citations

Book
29 Sep 2014
TL;DR: The basic concepts of asymptotic expansions, Mellin transform techniques, and the distributional approach are explained.
Abstract: Preface 1. Fundamental concepts of asymptotics 2. Classical procedures 3. Mellin transform techniques 4. The summability method 5. Elementary theory of distributions 6. The distributional approach 7. Uniform asymptotic expansions 8. Double integrals 9. Higher dimensional integrals Bibliography Symbol Index Author index Subject index.

1,061 citations

Journal ArticleDOI
TL;DR: A numerical inversion method for Laplace transforms, based on a Fourier series expansion developed by Durbin [5], is presented in this article, where the disadvantage of the inversion methods of that type, the encountered dependence of discretization and truncation error on the free parameters, is removed by the simultaneous application of a procedure for the reduction of the Discretization error, a method for accelerating the convergence of the Fourier Series and a procedure that computes approximately the "best" choice of the free parameter.

1,044 citations

Journal ArticleDOI
TL;DR: An accurate method is presented for the numerical inversion of Laplace transform, which is a natural continuation to Dubner and Abate's method, and the error bound on the inverse f{t) becomes independent of t, instead of being exponential in t.
Abstract: An accurate method is presented for the numerical inversion of Laplace transform, which is a natural continuation to Dubner and Abate's method. (Dubner and Abate, 1968). The advantages of this modified procedure are twofold: first, the error bound on the inverse f{t) becomes independent of t, instead of being exponential in t; second, and consequently, the trigonometric series obtained for fit) in terms of F(s) is valid on the whole period 2T of the series. As it is proved, this error bound can be set arbitrarily small, and it is always possible to get good results, even in rather difficult cases. Particular implementations and numerical examples are presented.

953 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202350
2022104
202163
202051
201960
201873