Optimal parameter selection in Weeks’ method for numerical Laplace transform inversion based on machine learning

Patrick O. Kano (Creator)
Moysey Brio (Contributor)
Jacob Bailey (Creator)

Agriculture and Life Sciences, College of
Mathematics
Applied Mathematics - GIDP

Dataset

Description

The Weeks method for the numerical inversion of the Laplace transform utilizes a Möbius transformation which is parameterized by two real quantities, σ and b. Proper selection of these parameters depends highly on the Laplace space function F(s) and is ...

Date made available	2021
Publisher	SAGE Journals

DOI
10.25384/sage.c.5357908.v1

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Creative Commons Attribution 4.0 International

1 Article

Optimal parameter selection in Weeks’ method for numerical Laplace transform inversion based on machine learning
Kano, P. O., Brio, M. & Bailey, J., 2021, In: Journal of Algorithms and Computational Technology. 15
Research output: Contribution to journal › Article › peer-review

Open Access
4 Scopus citations

Optimal parameter selection in Weeks’ method for numerical Laplace transform inversion based on machine learning

Description

DOI

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Research output

Optimal parameter selection in Weeks’ method for numerical Laplace transform inversion based on machine learning

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