Adaptive Linear Discriminant Analysis Algorithm Applied to Motion Signal Classification in EEG Processing
Rui Xu, Haoyue Tang
Available Online July 2015.
- https://doi.org/10.2991/icismme-15.2015.82How to use a DOI?
- EEG; brain computer interface; aCSP algorithm; aLDA algorithm; LDA algorithm; updating coefficient.
- In view of the current development research on electroencephalograph (EEG) brain computer interface (BCI), which shall not be limited to use linear discriminant analysis (LDA) algorithm only. The brain computer interface that uses multi channel and multi type EEG signal is gradually fusing on other ways that can better reflect the brain activity. Based on the EEG computer interface technology, we can use adaptive linear discriminant analysis (aLDA) algorithm and human-computer interaction method, also regulate adaptive updating coefficient (UC) to reflect the brain thinking activity better. In this paper, we use adaptive common spatial pattern (aCSP) algorithm to extract feature and better classification algorithm to process the EEG, which can improve the efficiency, accuracy and stability of signal classification.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Rui Xu AU - Haoyue Tang PY - 2015/07 DA - 2015/07 TI - Adaptive Linear Discriminant Analysis Algorithm Applied to Motion Signal Classification in EEG Processing BT - First International Conference on Information Sciences, Machinery, Materials and Energy PB - Atlantis Press SP - 412 EP - 417 SN - 1951-6851 UR - https://doi.org/10.2991/icismme-15.2015.82 DO - https://doi.org/10.2991/icismme-15.2015.82 ID - Xu2015/07 ER -