Details of Research Outputs

TitleTensor-based blind fMRI source separation without the Gaussian noise assumption - A β-divergence approach
Author (Name in English or Pinyin)
Chatzichristos, C.1; Vandecapelle, M.1,2; Kofidis, E.3; Theodoridis, S.4,5; Lathauwer, L.D.1,2; Van Huffel, S.1
Date Issued2019-11-01
Source PublicationGlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings
Indexed BySCOPUS
Firstlevel Discipline计算机科学技术
Education discipline科技类
Published range国外学术期刊
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Document TypeJournal article
CollectionSchool of Science and Engineering
Co-First AuthorVandecapelle, M.
Corresponding AuthorChatzichristos, C.
1.KU Leuven, Department of Electrical Engineering (ESAT), Leuven, Belgium
2.KU Leuven Kulak, Group Science, Engineering and Technology, Kortrijk, Belgium
3.Dept. of Statistics and Insurance Science, University of Piraeus, Greece
4.Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens, Greece
5.Chinese University of Hong Kong, Shenzhen, China
Recommended Citation
GB/T 7714
Chatzichristos, C.,Vandecapelle, M.,Kofidis, al. Tensor-based blind fMRI source separation without the Gaussian noise assumption - A β-divergence approach[J]. GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings,2019.
APA Chatzichristos, C., Vandecapelle, M., Kofidis, E., Theodoridis, S., Lathauwer, L.D., & Van Huffel, S. (2019). Tensor-based blind fMRI source separation without the Gaussian noise assumption - A β-divergence approach. GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings.
MLA Chatzichristos, C.,et al."Tensor-based blind fMRI source separation without the Gaussian noise assumption - A β-divergence approach".GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings (2019).
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