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Coherence Estimation between EEG signals using Multiple Window Time-Frequency Analysis compared to Gaussian Kernels

Sandberg, Johan LU and Sandsten, Maria LU (2006) 14th European Signal Processing Conference (EUSIPCO 2006)
Abstract
It is believed that neural activity evoked by cognitive tasks is spatially correlated in certain frequency bands. The electroencephalogram (EEG) is highly affected by noise of large amplitude which calls for sophisticated time local coherence estimation methods.







In this paper we investigate different approaches to estimate time local coherence between two real valued signals. Our results indicate that the method using two dimensional Gaussian kernels has a slightly better average SNR compared to the multiple window approach. On the other hand, the multiple window approach has a more narrow SNR distribution and seems to perform better in the worst case.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Non-stationary, Time-Frequency-Analysis, EEG, Coherence
host publication
14th European Signal Processing Conference
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
14th European Signal Processing Conference (EUSIPCO 2006)
conference location
Florence, Italy
conference dates
2006-09-04 - 2006-09-08
external identifiers
  • scopus:84862629486
language
English
LU publication?
yes
id
b978dc31-2248-4429-b1c3-9a6cb31a2fbf (old id 601330)
alternative location
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981924.pdf
date added to LUP
2016-04-04 11:35:00
date last changed
2022-01-29 22:04:10
@inproceedings{b978dc31-2248-4429-b1c3-9a6cb31a2fbf,
  abstract     = {{It is believed that neural activity evoked by cognitive tasks is spatially correlated in certain frequency bands. The electroencephalogram (EEG) is highly affected by noise of large amplitude which calls for sophisticated time local coherence estimation methods.<br/><br>
<br/><br>
<br/><br>
<br/><br>
In this paper we investigate different approaches to estimate time local coherence between two real valued signals. Our results indicate that the method using two dimensional Gaussian kernels has a slightly better average SNR compared to the multiple window approach. On the other hand, the multiple window approach has a more narrow SNR distribution and seems to perform better in the worst case.}},
  author       = {{Sandberg, Johan and Sandsten, Maria}},
  booktitle    = {{14th European Signal Processing Conference}},
  keywords     = {{Non-stationary; Time-Frequency-Analysis; EEG; Coherence}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Coherence Estimation between EEG signals using Multiple Window Time-Frequency Analysis compared to Gaussian Kernels}},
  url          = {{http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981924.pdf}},
  year         = {{2006}},
}