An Optimal Inverse Laplace Transform Method Without Positive and Negative Overshoot – An Integral Based Interpretation

Illés Horváth, Zsófia Talyigás, M. Telek

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a numerical inverse Laplace transformation method without overshoot which is derived from matrix exponential (ME) distributions with minimal coefficient of variation. We discuss the properties of the method through an integral based interpretation of numerical inverse Laplace transformation methods belonging to the Abate–Whitt framework. Compared to the previously applied non-overshooting alternative, the “Erlang” method, the error of the proposed method improves from O(1/n) to O(1/n2) while it maintains the same computational complexity.

Original languageEnglish
Pages (from-to)87-104
Number of pages18
JournalElectronic Notes in Theoretical Computer Science
Volume337
DOIs
Publication statusPublished - May 9 2018

Fingerprint

Inverse Laplace Transform
Inverse transforms
Overshoot
Laplace transforms
Computational complexity
Laplace Transformation
Matrix Exponential
Coefficient of variation
Exponential distribution
Computational Complexity
Interpretation
Alternatives

Keywords

  • matrix exponential distribution
  • minimal coefficient of variation
  • numerical Inverse Laplace transformation
  • overshoot

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

An Optimal Inverse Laplace Transform Method Without Positive and Negative Overshoot – An Integral Based Interpretation. / Horváth, Illés; Talyigás, Zsófia; Telek, M.

In: Electronic Notes in Theoretical Computer Science, Vol. 337, 09.05.2018, p. 87-104.

Research output: Contribution to journalArticle

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