Efficient Thomson Spectral Estimator with Time-shifted Windows
(2019) 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 2019-May. p.4983-4987- 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... (More)
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.
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- author
- Reinhold, Isabella LU and Sandsten, Maria LU
- organization
- publishing date
- 2019-05
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- DPSS, Slepian functions, spectral leakage, variance, Welch method
- host publication
- 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
- volume
- 2019-May
- article number
- 8683588
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
- conference location
- Brighton, United Kingdom
- conference dates
- 2019-05-12 - 2019-05-17
- external identifiers
-
- scopus:85068991965
- ISBN
- 9781479981311
- DOI
- 10.1109/ICASSP.2019.8683588
- language
- English
- LU publication?
- yes
- id
- f116d368-6712-45bd-b77b-40aea151b739
- date added to LUP
- 2019-07-23 17:14:25
- date last changed
- 2022-04-26 03:41:55
@inproceedings{f116d368-6712-45bd-b77b-40aea151b739, abstract = {{<p>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.</p>}}, author = {{Reinhold, Isabella and Sandsten, Maria}}, booktitle = {{2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings}}, isbn = {{9781479981311}}, keywords = {{DPSS; Slepian functions; spectral leakage; variance; Welch method}}, language = {{eng}}, pages = {{4983--4987}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Efficient Thomson Spectral Estimator with Time-shifted Windows}}, url = {{http://dx.doi.org/10.1109/ICASSP.2019.8683588}}, doi = {{10.1109/ICASSP.2019.8683588}}, volume = {{2019-May}}, year = {{2019}}, }