Time-varying nonlinear causality detection using regularized orthogonal least squares and multi-wavelets with applications to EEG

Li, Y, Lei, M., Guo, Y. et al. (2 more authors) (2018) Time-varying nonlinear causality detection using regularized orthogonal least squares and multi-wavelets with applications to EEG. IEEE Access, 6. pp. 17826-17840.

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Copyright, Publisher and Additional Information: © 2018 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: Granger causality; nonlinear time-varying systems; parametric estimation; multi-wavelets; regularized orthogonal least squares (ROLS); EEG
Dates:
  • Published: 26 March 2018
  • Accepted: 19 March 2018
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: 27 Mar 2018 10:10
Last Modified: 17 Apr 2018 15:28
Published Version: https://doi.org/10.1109/ACCESS.2018.2818789
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/ACCESS.2018.2818789

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