Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISSNIP.2007.4496874
Title: Recursive fisher linear discriminant for BCI applications
Authors: Huang, D.
Xiang, C. 
Ge, S.S. 
Issue Date: 2007
Source: Huang, D., Xiang, C., Ge, S.S. (2007). Recursive fisher linear discriminant for BCI applications. Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP : 383-388. ScholarBank@NUS Repository. https://doi.org/10.1109/ISSNIP.2007.4496874
Abstract: A novel recursive procedure for extracting discriminant features, termed Recursive Fisher Linear Discriminant (RFLD), is applied to brain-computer interface (BCI) problems. Compared to traditional Fisher Linear Discriminant (FLD), RFLD relaxes the constraint on the total number of features that can be extracted. The new RFLD has been tested on motor imagery classification with the electrocorticography (ECoG) signals. The resulting improvement of performance by the new feature extraction scheme suggests the effectiveness of our method. © 2007 IEEE.
Source Title: Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP
URI: http://scholarbank.nus.edu.sg/handle/10635/51241
ISBN: 1424415020
DOI: 10.1109/ISSNIP.2007.4496874
Appears in Collections:Staff Publications

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