Fourier Expansion Method for Positive Real Approximation of Sampled Frequency Data
Summary :
Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.9 pp.1937-1944
- Publication Date
- 2014/09/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.1937
- Type of Manuscript
- PAPER
- Category
- Circuit Theory
Authors
Yuichi TANJI
Kagawa University
Keyword
Latest Issue
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Yuichi TANJI, "Fourier Expansion Method for Positive Real Approximation of Sampled Frequency Data" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 9, pp. 1937-1944, September 2014, doi: 10.1587/transfun.E97.A.1937.
Abstract: Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.1937/_p
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@ARTICLE{e97-a_9_1937,
author={Yuichi TANJI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fourier Expansion Method for Positive Real Approximation of Sampled Frequency Data},
year={2014},
volume={E97-A},
number={9},
pages={1937-1944},
abstract={Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.},
keywords={},
doi={10.1587/transfun.E97.A.1937},
ISSN={1745-1337},
month={September},}
Copy
TY - JOUR
TI - Fourier Expansion Method for Positive Real Approximation of Sampled Frequency Data
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1937
EP - 1944
AU - Yuichi TANJI
PY - 2014
DO - 10.1587/transfun.E97.A.1937
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2014
AB - Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.
ER -
English
