Block adaptive filters with deterministic reference inputs for event-related signals: BLMS and BRLS
Adaptive estimation of the linear coefficient vector in truncated expansions is considered for the purpose of modeling noisy, recurrent signals. Two different criteria are studied for block-wise processing of the signal: the mean square error (MSE) and the least squares (LS) error. The block LMS (BLMS) algorithm, being the solution of the steepest descent strategy for minimizing the MSE, is shown
