Exploring sampling in the detection of multicategory EEG signals
Article
Article Title | Exploring sampling in the detection of multicategory EEG signals |
---|---|
ERA Journal ID | 44832 |
Article Category | Article |
Authors | Siuly, Siuly (Author), Kabir, Enamul (Author), Wang, Hua (Author) and Zhang, Yanchun (Author) |
Journal Title | Computational and Mathematical Methods in Medicine |
Journal Citation | 2015 |
Number of Pages | 12 |
Year | 2015 |
Publisher | Hindawi Publishing Corporation |
Place of Publication | New York, NY. United States |
ISSN | 1748-670X |
1748-6718 | |
Digital Object Identifier (DOI) | https://doi.org/10.1155/2015/576437 |
Web Address (URL) | http://www.hindawi.com/journals/cmmm/2015/576437/ |
Abstract | The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored. In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period.The |
Keywords | sampling, random sampling (RS), optimal allocation sampling (OS) |
ANZSRC Field of Research 2020 | 400399. Biomedical engineering not elsewhere classified |
Public Notes | Copyright © 2015 Siuly Siuly et al. This is an open access article distributed under the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | Victoria University |
School of Agricultural, Computational and Environmental Sciences |
https://research.usq.edu.au/item/q306q/exploring-sampling-in-the-detection-of-multicategory-eeg-signals
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