Automated EEG signal classification using chaotic local binary pattern
Article
| Article Title | Automated EEG signal classification using chaotic local binary pattern |
|---|---|
| ERA Journal ID | 17852 |
| Article Category | Article |
| Authors | Tuncer,Turker, Dogan, Sengul and Acharya, U. Rajendra |
| Journal Title | Expert Systems with Applications |
| Journal Citation | 182 |
| Article Number | 115175 |
| Number of Pages | 8 |
| Year | 2021 |
| Publisher | Elsevier |
| Place of Publication | United Kingdom |
| ISSN | 0957-4174 |
| 1873-6793 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eswa.2021.115175 |
| Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0957417421006138 |
| Abstract | Background Method Results Conclusion |
| Keywords | EEG classification; Fractal hypercube graph pattern; Iterative neighborhood component analysis ; Epilepsy seizure detection |
| ANZSRC Field of Research 2020 | 400306. Computational physiology |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | Firat University, Turkey |
| Ngee Ann Polytechnic, Singapore | |
| Singapore University of Social Sciences (SUSS), Singapore | |
| Asia University, Taiwan |
https://research.usq.edu.au/item/z1w3z/automated-eeg-signal-classification-using-chaotic-local-binary-pattern
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