This website uses cookies to store user session information. By using our website you consent to our terms of use. Read more
I agree

Surrogate Data Method Requires End-Matched Segmentation of Electroencephalographic Signals to Estimate Non-linearity

Päeske, L.; Bachmann, M.; Põld, T.; de Oliveira, S. P. M.; Lass, J.; Raik, J.; Hinrikus, H. (2018). Surrogate Data Method Requires End-Matched Segmentation of Electroencephalographic Signals to Estimate Non-linearity. Frontiers in Physiology, 9, ARTN 1350. DOI: 10.3389/fphys.2018.01350.
article in a journal
Päeske, L.; Bachmann, M.; Põld, T.; de Oliveira, S. P. M.; Lass, J.; Raik, J.; Hinrikus, H.
  • English
Frontiers in Physiology
LAUSANNE
1664-042X
9
9
2018
ARTN 1350
9
Published
1.1. Scholarly articles indexed by Web of Science Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citation Index, Emerging Sources Citation Index and/or indexed by Scopus (excluding chapters in books)
Yes
gold
Attribution (CC BY)
WOS

Reference to the full text

doi.org/10.3389/fphys.2018.01350