The noise handling properties of the Talbot algorithm for numerically inverting the Laplace transform

This paper examines the noise handling properties of three of the most widely used algorithms for numerically inverting the Laplace transform. After examining the genesis of the algorithms, their error handling properties are evaluated through a series of standard test functions in which noise is ad...

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Bibliographic Details
Main Authors: Colin L Defreitas, Steve J Kane
Format: Article
Language:English
Published: SAGE Publishing 2018-09-01
Series:Journal of Algorithms & Computational Technology
Online Access:https://doi.org/10.1177/1748301818797069
Description
Summary:This paper examines the noise handling properties of three of the most widely used algorithms for numerically inverting the Laplace transform. After examining the genesis of the algorithms, their error handling properties are evaluated through a series of standard test functions in which noise is added to the inverse transform. Comparisons are then made with the exact data. Our main finding is that the for “noisy data”, the Talbot inversion algorithm performs with greater accuracy when compared to the Fourier series and Stehfest numerical inversion schemes as they are outlined in this paper.
ISSN:1748-3026