Partial-update adaptive filters for event-related potentials denoising

In the present study, the adaptive Fourier linear combiner is used to denoise the single-trial event-related potential signals. The Least Mean Square algorithm, the Normalized Least Mean Square algorithm and the Recursive Least Square algorithm are compared with different approaches to partial coefficient updates: periodic partial updates, sequential partial updates, stochastic partial updates, M-max updates and selective partial updates. The different approaches are compared in term of convergence speed, tracking capability and computational complexity. The methods are also validated on a real human P300 recording.