EFFICIENT ADAPTIVE ALGORITHMS FOR ARX IDENTIFICATION

In this paper two efficient adaptive algorithmic families are developed for multichannel combiners characterized by unequal memory lengths for each input channel. The prewindowed, the covariance, as well as the sliding window case are treated. The new algorithms are based on two different updating procedures for the associated Kalman gain vector by employing suitable permutation matrices. Both algorithms are applicable to adaptive ARX system identification, to adaptive control, and to the design of decision-feedback equalizers. Simulations are included.