Name
Abstract | ||
|---|---|---|
Brain Computer Interface BCI is a type of human-computer relationship research that directly translates electrical activity of brain into commands that can rule equipment and create novel communication channel for muscular disabled patients. In this study, in order to overcome shortcoming of Singular Value Decomposition in Extreme Learning Machine, iteratively optimized neuron numbered QR Decomposition technique with different approaches are proposed. QR Decomposition Extreme Learning Machine technique based P300 event-related potential BCI application that achieves almost % 100 classification accuracy with milliseconds is presented. QR decomposition based ELM and novel feature extraction method named Multi Order Difference Plot MoDP techniques are milestones of proposed BCI system. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-26535-3_33 | ICONIP |
Keywords | Field | DocType |
Brain computer interface,P300,QR decomposition,MoDP method,Iteratively optimized neuron number | Singular value decomposition,Pattern recognition,Computer science,Extreme learning machine,Brain–computer interface,Communication channel,Feature extraction,Speech recognition,Artificial intelligence,Machine learning,QR decomposition | Conference |
Volume | ISSN | Citations |
9490 | 0302-9743 | 2 |
PageRank | References | Authors |
0.45 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yakup Kutlu | 1 | 15 | 4.86 |
| Apdullah Yayik | 2 | 2 | 2.14 |
| Esen Yildirim | 3 | 19 | 4.18 |
| Serdar Yildirim | 4 | 523 | 30.10 |