@inproceedings{scholars7174,
           title = {Single trial visual evoked potential extraction using fast PLS},
           pages = {419--422},
             doi = {10.1109/ICSIPA.2015.7412227},
         journal = {IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings},
            year = {2016},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
            note = {cited By 0; Conference of 4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015 ; Conference Date: 19 October 2015 Through 21 October 2015; Conference Code:119504},
            isbn = {9781479989966},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971672844&doi=10.1109\%2fICSIPA.2015.7412227&partnerID=40&md5=60a7c8a25502d15e60bd13ca0fb5e02c},
        abstract = {This paper evaluates the single trial extraction of Visual Evoked Potential (VEP) signal. Single trial extraction of VEP contributes in the integration of fMRI-EEG application as well as in the Brain Computer Interface application. The extraction is performed by using the Fast Partial Least Square (PLS) algorithm. The extraction of the desired VEP signals, both in artificial and real Electroencephalography (EEG) signal is quantified. Moreover, the latency or average error rates of P100, P200 and P300 in the artificial signal have been measured. The results illustrate the advantages and drawbacks of the algorithm in the single trial VEP extraction case. {\^A}{\copyright} 2015 IEEE.},
          author = {Yanti, D. K. and Yusoff, M. Z. and Bekdash, M. and Asirvadam, V. S.},
        keywords = {Brain computer interface; Electroencephalography; Electrophysiology; Extraction; Interfaces (computer); Least squares approximations; Principal component analysis, Artificial signals; Average errors; Brain-computer interface applications; Partial least square (PLS); Partial least square algorithms; Single trial; Visual evoked potential, Image processing}
}