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Computational Intelligence for Brain Computer Interface Guest Editorial.

, , and . IEEE Comput. Intell. Mag., 11 (1): 18 (2016)

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Application of rough set-based neuro-fuzzy system in NIRS-based BCI for assessing numerical cognition in classroom., , , , , and . IJCNN, page 1-7. IEEE, (2010)Improving session-to-session transfer performance of motor imagery-based BCI using adaptive extreme learning machine., , , and . EMBC, page 2188-2191. IEEE, (2013)Estimation of glance from EEG for cursor control., , and . EMBC, page 2919-2923. IEEE, (2013)Transcranial direct current stimulation and EEG-based motor imagery BCI for upper limb stroke rehabilitation., , , , , , and . EMBC, page 4128-4131. IEEE, (2012)Neural decoding of movement targets by unsorted spike trains., , and . ICASSP, page 954-958. IEEE, (2013)Towards improvement of MI-BCI performance of subjects with BCI deficiency., , , and . NER, page 17-20. IEEE, (2015)Neural representations of movement intentions during brain-controlled self-motion., , , , , , and . NER, page 228-231. IEEE, (2015)Enhancing the Extraction of Interpretable Information for Ischemic Stroke Imaging from Deep Neural Networks., , , and . CoRR, (2019)Dynamically Weighted Classification with Clustering to tackle non-stationarity in Brain computer Interfacing., , , , , and . IJCNN, page 1-6. IEEE, (2012)Joint feature re-extraction and classification using an iterative semi-supervised support vector machine algorithm., and . Mach. Learn., 71 (1): 33-53 (2008)