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Pole Recovery From Noisy Data on Imaginary Axis

Pole Recovery From Noisy Data on Imaginary Axis This note proposes an algorithm for identifying the poles and residues of a meromorphic function from its noisy values on the imaginary axis. The algorithm uses Möbius transform and Prony’s method in the frequency domain. Numerical results are provided to demonstrate the performance of the algorithm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Scientific Computing Springer Journals

Pole Recovery From Noisy Data on Imaginary Axis

Journal of Scientific Computing , Volume 92 (3) – Sep 1, 2022

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References (22)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022
ISSN
0885-7474
eISSN
1573-7691
DOI
10.1007/s10915-022-01963-z
Publisher site
See Article on Publisher Site

Abstract

This note proposes an algorithm for identifying the poles and residues of a meromorphic function from its noisy values on the imaginary axis. The algorithm uses Möbius transform and Prony’s method in the frequency domain. Numerical results are provided to demonstrate the performance of the algorithm.

Journal

Journal of Scientific ComputingSpringer Journals

Published: Sep 1, 2022

Keywords: Rational approximation; Prony’s method; Analytic continuation; 30B40; 93B55

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