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Highly Accurate and Noise-Robust Phase Delay Estimation using Multitaper Reassignment

Akesson, Maria LU ; Keding, Oskar LU ; Reinhold, Isabella LU and Sandsten, Maria LU (2023) 31st European Signal Processing Conference, EUSIPCO 2023 In European Signal Processing Conference p.1763-1767
Abstract

The recently developed Phase-Scaled Reassignment (PSR) can estimate phase-difference between two oscillating transient signals with high accuracy. However, in low signal-to-noise ratios (SNRs) the performance of commonly applied reassignment techniques is known to deteriorate. In order to reduce variance in low SNR, we propose a multitaper PSR (mtPSR) method for phase-difference estimation between Gaussian transient signals. Three possible variations of this method are investigated and evaluated, mtPSR1, mtPSR2, and mtPSR3. All three variations are shown to outperform state-of-the-art methods and improve estimation accuracy in low SNR. The mtPSR1 is superior in terms of computational efficiency while the mtPSR3 achieves the highest... (More)

The recently developed Phase-Scaled Reassignment (PSR) can estimate phase-difference between two oscillating transient signals with high accuracy. However, in low signal-to-noise ratios (SNRs) the performance of commonly applied reassignment techniques is known to deteriorate. In order to reduce variance in low SNR, we propose a multitaper PSR (mtPSR) method for phase-difference estimation between Gaussian transient signals. Three possible variations of this method are investigated and evaluated, mtPSR1, mtPSR2, and mtPSR3. All three variations are shown to outperform state-of-the-art methods and improve estimation accuracy in low SNR. The mtPSR1 is superior in terms of computational efficiency while the mtPSR3 achieves the highest accuracy. The mtPSR technique is also shown to be robust to model assumptions. An example of phase delay estimates of the electrical signals measured from the brain reveals promising results.

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author
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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
series title
European Signal Processing Conference
pages
5 pages
publisher
European Signal Processing Conference, EUSIPCO
conference name
31st European Signal Processing Conference, EUSIPCO 2023
conference location
Helsinki, Finland
conference dates
2023-09-04 - 2023-09-08
external identifiers
  • scopus:85178361574
ISSN
2219-5491
ISBN
9789464593600
DOI
10.23919/EUSIPCO58844.2023.10289747
language
English
LU publication?
yes
id
ee4afe6d-95fd-47cc-a879-cfe07ab5f14b
date added to LUP
2024-01-08 10:44:37
date last changed
2024-01-08 10:45:25
@inproceedings{ee4afe6d-95fd-47cc-a879-cfe07ab5f14b,
  abstract     = {{<p>The recently developed Phase-Scaled Reassignment (PSR) can estimate phase-difference between two oscillating transient signals with high accuracy. However, in low signal-to-noise ratios (SNRs) the performance of commonly applied reassignment techniques is known to deteriorate. In order to reduce variance in low SNR, we propose a multitaper PSR (mtPSR) method for phase-difference estimation between Gaussian transient signals. Three possible variations of this method are investigated and evaluated, mtPSR1, mtPSR2, and mtPSR3. All three variations are shown to outperform state-of-the-art methods and improve estimation accuracy in low SNR. The mtPSR1 is superior in terms of computational efficiency while the mtPSR3 achieves the highest accuracy. The mtPSR technique is also shown to be robust to model assumptions. An example of phase delay estimates of the electrical signals measured from the brain reveals promising results.</p>}},
  author       = {{Akesson, Maria and Keding, Oskar and Reinhold, Isabella and Sandsten, Maria}},
  booktitle    = {{31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings}},
  isbn         = {{9789464593600}},
  issn         = {{2219-5491}},
  language     = {{eng}},
  pages        = {{1763--1767}},
  publisher    = {{European Signal Processing Conference, EUSIPCO}},
  series       = {{European Signal Processing Conference}},
  title        = {{Highly Accurate and Noise-Robust Phase Delay Estimation using Multitaper Reassignment}},
  url          = {{http://dx.doi.org/10.23919/EUSIPCO58844.2023.10289747}},
  doi          = {{10.23919/EUSIPCO58844.2023.10289747}},
  year         = {{2023}},
}