On the Laguerre method for numerically inverting Laplace transforms

On the Laguerre method for numerically inverting Laplace transforms

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Article ID: iaor19972070
Country: United States
Volume: 8
Issue: 4
Start Page Number: 413
End Page Number: 427
Publication Date: Oct 1996
Journal: INFORMS Journal On Computing
Authors: , ,
Keywords: computational analysis
Abstract:

The Laguerre method for numerically inverting Laplace transforms is an old established method based on the 1935 Tricomi-Widder theorem, which shows (under suitable regularity conditions) that the desired function can be represented as a weighted sum of Laguerre functions, where the weights are coefficients of a generating function constructed from the Laplace transform using a bilinear transformation. The authors present a new variant of the Laguerre method based on: (i) using the present previously developed variant of the Fourier-series method to calculate the coefficients of the Laguerre generating function; (ii) developing systematic methods for scaling; and (iii) using Wynn’s •-algorithm to accelerate convergence of the Laguerre series when the Laguerre coefficients do not converge to zero geometrically fast. These contributions significantly expand the class of transforms that can be effectively inverted by the Laguerre method. The authors provide insight into the slow convergence of the Laguerre coefficients as well as propose a remedy. Before acceleration, the rate of convergence can often be determined from the Laplace transform by applying Darboux’s theorem. Even when the Laguerre coefficients converge to zero geometrically fast, it can be difficult to calculate the desired functions for large arguments because of roundoff errors. The authors solve this problem by calculating very small Laguerre coefficients with low relative error through appropriate scaling. They also develop another acceleration technique for the case in which the Laguerre coefficients converge to zero geometrically fast. The authors illustrate the effectiveness of the present algorithm through numerical examples.

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