Wei, H.L., Liu, J. and Billings, S.A. (2008) Time-varying parametric modelling and time-dependent spectral characterisation with applications to EEG signals using multi-wavelets. Research Report. ACSE Research Report no. 977 . Automatic Control and Systems Engineering, University of Sheffield
Abstract
A new time-varying autoregressive (TVAR) modelling approach is proposed for nonstationary signal processing and analysis, with application to EEG data modelling and power spectral estimation. In the new parametric modelling framework, the time-dependent coefficients of the TVAR model are represented using a novel multi-wavelet decomposition scheme. The time-varying modelling problem is then reduced to regression selection and parameter estimation, which can be effectively resolved by using a forward orthogonal regression algorithm. Two examples, one for an artificial signal and another for an EEG signal, are given to show the effectiveness and applicability of the new TVAR modelling method.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances. |
Keywords: | Time-varying models, autoregressive (AR) models, system identification, model structure detection, orthogonal least squares, time-dependent spectra, wavelets, EEG. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports |
Depositing User: | Miss Anthea Tucker |
Date Deposited: | 15 Oct 2012 14:44 |
Last Modified: | 06 Jun 2014 02:48 |
Status: | Published |
Publisher: | Automatic Control and Systems Engineering, University of Sheffield |
Series Name: | ACSE Research Report no. 977 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:74634 |