@inproceedings{d10d82d89c154131863884a37e07d695,
title = "Adaptive classification by hybrid EKF with truncated filtering: Brain computer interfacing",
abstract = "This paper proposes a robust algorithm for adaptive modelling of EEG signal classification using a modified Extended Kalman Filter (EKF). This modified EKF combines Radial Basis functions (RBF) and Autoregressive (AR) modeling and obtains better classification performance by truncating the filtering distribution when new observations are very informative.",
keywords = "Extended Kalman filter, Informative observation, Logistic classification, Truncated filtering",
author = "Yoon, {Ji Won} and Roberts, {Stephen J.} and Matthew Dyson and Gan, {John Q.}",
note = "Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 9th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2008 ; Conference date: 02-11-2008 Through 05-11-2008",
year = "2008",
doi = "10.1007/978-3-540-88906-9_47",
language = "English",
isbn = "3540889051",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "370--377",
booktitle = "Intelligent Data Engineering and Automated Learning - IDEAL 2008 - 9th International Conference, Proceedings",
}