Efficient Thomson Spectral Estimator with Time-shifted Windows

Isabella Reinhold; Maria Sandsten

doi:10.1109/ICASSP.2019.8683588

Efficient Thomson Spectral Estimator with Time-shifted Windows

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

In this paper optimal spectral analysis window shapes, using weighted discrete prolate spheroidal sequences as basis functions, are proposed. These windows are not typically positive or even. The windows are time-shifted, combining the computational efficiency of the Welch method and the appealing property of predefined frequency resolution of the Thomson spectral estimator. The parameters of the optimal windows are found by minimising the resulting spectral covariances and optimising the window overlap, for the predetermined frequency resolution and number of windows. The windows are found to have low side lobes, giving small spectral leakage, and the final spectral estimate gives close to optimal variance reduction, i.e. the covariance between different sub-spectra is very small.

Original language	English
Title of host publication	2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	4983-4987
Number of pages	5
Volume	2019-May
ISBN (Electronic)	9781479981311
DOIs	https://doi.org/10.1109/ICASSP.2019.8683588
Publication status	Published - 2019 May
Event	44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom Duration: 2019 May 12 → 2019 May 17

Conference

Conference	44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/Territory	United Kingdom
City	Brighton
Period	2019/05/12 → 2019/05/17

Subject classification (UKÄ)

Signal Processing
Probability Theory and Statistics

Free keywords

DPSS
Slepian functions
spectral leakage
variance
Welch method

Access to Document

10.1109/ICASSP.2019.8683588

Cite this

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title = "Efficient Thomson Spectral Estimator with Time-shifted Windows",

abstract = "In this paper optimal spectral analysis window shapes, using weighted discrete prolate spheroidal sequences as basis functions, are proposed. These windows are not typically positive or even. The windows are time-shifted, combining the computational efficiency of the Welch method and the appealing property of predefined frequency resolution of the Thomson spectral estimator. The parameters of the optimal windows are found by minimising the resulting spectral covariances and optimising the window overlap, for the predetermined frequency resolution and number of windows. The windows are found to have low side lobes, giving small spectral leakage, and the final spectral estimate gives close to optimal variance reduction, i.e. the covariance between different sub-spectra is very small.",

keywords = "DPSS, Slepian functions, spectral leakage, variance, Welch method",

author = "Isabella Reinhold and Maria Sandsten",

year = "2019",

month = may,

doi = "10.1109/ICASSP.2019.8683588",

language = "English",

volume = "2019-May",

pages = "4983--4987",

booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",

}

Reinhold, I & Sandsten, M 2019, Efficient Thomson Spectral Estimator with Time-shifted Windows. in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. vol. 2019-May, 8683588, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 4983-4987, 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, Brighton, United Kingdom, 2019/05/12. https://doi.org/10.1109/ICASSP.2019.8683588

Efficient Thomson Spectral Estimator with Time-shifted Windows. / Reinhold, Isabella; Sandsten, Maria.
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Vol. 2019-May IEEE - Institute of Electrical and Electronics Engineers Inc., 2019. p. 4983-4987 8683588.

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Efficient Thomson Spectral Estimator with Time-shifted Windows

AU - Reinhold, Isabella

AU - Sandsten, Maria

PY - 2019/5

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N2 - In this paper optimal spectral analysis window shapes, using weighted discrete prolate spheroidal sequences as basis functions, are proposed. These windows are not typically positive or even. The windows are time-shifted, combining the computational efficiency of the Welch method and the appealing property of predefined frequency resolution of the Thomson spectral estimator. The parameters of the optimal windows are found by minimising the resulting spectral covariances and optimising the window overlap, for the predetermined frequency resolution and number of windows. The windows are found to have low side lobes, giving small spectral leakage, and the final spectral estimate gives close to optimal variance reduction, i.e. the covariance between different sub-spectra is very small.

AB - In this paper optimal spectral analysis window shapes, using weighted discrete prolate spheroidal sequences as basis functions, are proposed. These windows are not typically positive or even. The windows are time-shifted, combining the computational efficiency of the Welch method and the appealing property of predefined frequency resolution of the Thomson spectral estimator. The parameters of the optimal windows are found by minimising the resulting spectral covariances and optimising the window overlap, for the predetermined frequency resolution and number of windows. The windows are found to have low side lobes, giving small spectral leakage, and the final spectral estimate gives close to optimal variance reduction, i.e. the covariance between different sub-spectra is very small.

KW - DPSS

KW - Slepian functions

KW - spectral leakage

KW - variance

KW - Welch method

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DO - 10.1109/ICASSP.2019.8683588

M3 - Paper in conference proceeding

AN - SCOPUS:85068991965

VL - 2019-May

SP - 4983

EP - 4987

BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019

Y2 - 12 May 2019 through 17 May 2019

ER -

Efficient Thomson Spectral Estimator with Time-shifted Windows

Abstract

Conference

Subject classification (UKÄ)

Free keywords

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Spectral Analysis for Signal Detection and Classification: Reducing Variance and Extracting Features

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