Suwansawang, Sopapun and Halliday, David M. orcid.org/0000-0001-9957-0983 (2020) Wavelet-based method for coherence analysis with suppression of low frequency envelope modulation in non-stationary signals. In: 2020 8th International Electrical Engineering Congress, iEECON 2020. 8th International Electrical Engineering Congress, iEECON 2020, 04-06 Mar 2020 2020 8th International Electrical Engineering Congress, iEECON 2020 . IEEE , THA
Abstract
Techniques for non-stationary signal analysis are important in understanding dynamical behaviour of complex systems. Time-frequency coherence is widely used to analyse time-varying characteristics in non-stationary signals. This paper presents wavelet-based methods, using Airy wavelet, to estimate coherence. We incorporate a novel technique for removal of low frequency components due to envelope modulation in non-stationary signals. The technique is demonstrated on synthetic and real neurophysiological data. Results not only provide a clear description of desired features in non-stationary signals, but also suppress low frequency components due to envelope modulation. Our novel technique shows an effectiveness in extracting features hidden within the signals. It may lead to improved results in coherence analysis of medical, biological, physical and geophysical data containing low frequency envelope modulation besides non-stationarities.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Publisher Copyright: © 2020 IEEE. |
Keywords: | analytic wavelets,baseline correction,non-stationary analysis,signal processing |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 25 Jan 2022 11:40 |
Last Modified: | 16 Oct 2024 11:16 |
Published Version: | https://doi.org/10.1109/iEECON48109.2020.229461 |
Status: | Published |
Publisher: | IEEE |
Series Name: | 2020 8th International Electrical Engineering Congress, iEECON 2020 |
Identification Number: | 10.1109/iEECON48109.2020.229461 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182883 |