no code implementations • 6 Jul 2022 • Elnaz Banan Sadeghian
In this paper, we propose to replace the conventional communication-theoretic multiple-input multiple-output equalizer in the GPRML architecture with a neural network equalizer for better adaption to the nonlinearity of the underlying channel.
no code implementations • 19 Apr 2022 • Navid Ayoobi, Elnaz Banan Sadeghian
Detecting the salient parts of motor-imagery electroencephalogram (MI-EEG) signals can enhance the performance of the brain-computer interface (BCI) system and reduce the computational burden required for processing lengthy MI-EEG signals.
no code implementations • 19 Apr 2022 • Navid Ayoobi, Elnaz Banan Sadeghian
Developing a subject-independent MI-BCI system to reduce the calibration phase is still challenging due to the subject-dependent characteristics of the MI signals.
no code implementations • 12 Apr 2022 • Navid Ayoobi, Elnaz Banan Sadeghian
In a self-paced motor-imagery brain-computer interface (MI-BCI), the onsets of the MI commands presented in a continuous electroencephalogram (EEG) signal are unknown.