A multiple beta wavelet-based locally regularized ultraorthogonal forward regression algorithm for time-varying system identification with applications to EEG

Li, Y., Zhang, J., Cui, W. et al. (2 more authors) (2019) A multiple beta wavelet-based locally regularized ultraorthogonal forward regression algorithm for time-varying system identification with applications to EEG. IEEE Transactions on Instrumentation and Measurement. ISSN 0018-9456

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: EEG; locally regularized ultra-orthogonal forward regression (LRUOFR); multiple beta wavelet (MBW); parametric estimation; system identification
Dates:
  • Accepted: 3 April 2019
  • Published (online): 9 October 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 18 Apr 2019 09:12
Last Modified: 18 Oct 2019 07:59
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: https://doi.org/10.1109/TIM.2019.2907036

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