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pro vyhledávání: '"Walid Mohammed Ahmed Ayedh"'
Publikováno v:
IEEE Access, Vol 7, Pp 40959-40968 (2019)
The conventional autoregressive (AR) model has been widely applied in the various electroencephalogram (EEG) analyses such as spectrum estimation, waveform fittings, and in classification tasks. Nevertheless, evoked EEG is usually inevitably contamin
Externí odkaz:
https://doaj.org/article/77917e0272d8413bb2d5f0d4378a0c10
Autor:
Lin Jiang, Peng Xu, Chunli Chen, Dezhong Yao, Walid Mohammed Ahmed Ayedh, Peiyang Li, Joyce Chelangat Bore, Zehong Cao, Dennis Joe Harmah
EEG inverse problem is underdetermined, which poses a long standing challenge in Neuroimaging. The combination of source-imaging and analysis of cortical directional networks enables us to noninvasively explore the underlying neural processes. Howeve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a389a1004ed8431fb8b36517ed12a266
https://hdl.handle.net/10453/154800
https://hdl.handle.net/10453/154800
Publikováno v:
IEEE Access, Vol 7, Pp 40959-40968 (2019)
The conventional autoregressive (AR) model has been widely applied in the various electroencephalogram (EEG) analyses such as spectrum estimation, waveform fittings, and in classification tasks. Nevertheless, evoked EEG is usually inevitably contamin