A Fast Algorithm for KSVD in EEG Signal Analysis

EEG signal analysis plays a very important role in medical and brain science research, based on the acquisition of steady-state visual evoked potentials (SSVEP) in EEG signals with a brain-computer interface (BCI) system, this paper analyses its sparse characteristics using KSVD algorithms and proposes a fast algorithm based on Fast Fourier transform (FFT) , this algorithm converts the very time-consuming inner-products operation in the matching pursuit (MP) algorithm used in the KSVD method into cross-correlation, significantly increases the speed of signal analysis, simulation results verified the effectiveness of the method.