Oskoei, MA and Gan, JQ and Huosheng Hu (2009) Adaptive schemes applied to online SVM for BCI data classification. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. pp. 2600-2603. DOI https://doi.org/10.1109/iembs.2009.5335328
Oskoei, MA and Gan, JQ and Huosheng Hu (2009) Adaptive schemes applied to online SVM for BCI data classification. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. pp. 2600-2603. DOI https://doi.org/10.1109/iembs.2009.5335328
Oskoei, MA and Gan, JQ and Huosheng Hu (2009) Adaptive schemes applied to online SVM for BCI data classification. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. pp. 2600-2603. DOI https://doi.org/10.1109/iembs.2009.5335328
Abstract
This paper evaluates supervised and unsupervised adaptive schemes applied to online support vector machine (SVM) that classifies BCI data. Online SVM processes fresh samples as they come and update existing support vectors without referring to pervious samples. It is shown that the performance of online SVM is similar to that of the standard SVM, and both supervised and unsupervised schemes improve the classification hit rate. ©2009 IEEE.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Brain; Humans; Brain Mapping; Models, Statistical; Reproducibility of Results; Equipment Design; Computational Biology; Algorithms; Fuzzy Logic; Artificial Intelligence; Internet; Signal Processing, Computer-Assisted; Software; User-Computer Interface; Pattern Recognition, Automated |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 12 Dec 2012 21:09 |
| Last Modified: | 23 Sep 2022 18:28 |
| URI: | http://repository.essex.ac.uk/id/eprint/4144 |