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A Procedure for Laplace Transform Inversion Based on Smoothing Exponential-Polynomial Splines

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Numerical Computations: Theory and Algorithms (NUMTA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11973))

Abstract

Multi-exponential decaying data are very frequent in applications and a continuous description of this type of data allows the use of mathematical tools for data analysis such as the Laplace Transform (LT). In this work a numerical procedure for the Laplace Transform Inversion (LTI) of multi-exponential decaying data is proposed. It is based on a new fitting model, that is a smoothing exponential-polynomial spline with segments expressed in Bernstein-like bases. A numerical experiment concerning the application of a LTI method applied to our spline model highlights that it is very promising in the LTI of exponential decay data.

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Acknowledgements

The authors are members of the INdAM Research group GNCS and of the Research ITalian network on Approximation (RITA).

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Authors and Affiliations

  1. Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples, Italy

    Rosanna Campagna

  2. Department of Industrial Engineering, University of Florence, Florence, Italy

    Costanza Conti

  3. Department of Mathematics and Applications “R. Caccioppoli”, University of Naples Federico II, Naples, Italy

    Salvatore Cuomo

Authors
  1. Rosanna Campagna
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  2. Costanza Conti
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  3. Salvatore Cuomo
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Corresponding author

Correspondence to Rosanna Campagna .

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Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Yaroslav D. Sergeyev

  2. University of Calabria, Rende, Italy

    Dmitri E. Kvasov

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Campagna, R., Conti, C., Cuomo, S. (2020). A Procedure for Laplace Transform Inversion Based on Smoothing Exponential-Polynomial Splines. In: Sergeyev, Y., Kvasov, D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science(), vol 11973. Springer, Cham. https://doi.org/10.1007/978-3-030-39081-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-39081-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39080-8

  • Online ISBN: 978-3-030-39081-5

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