A new multichannel recursive least squares algorithm for very robust and efficient adaptive filtering

In this paper, a new multichannel recursive least squares (MRLS) adaptive a lgorithm is presented which has a number of very interesting properties. Th e proposed computational scheme performs adaptive filtering via the use of a finite window, where the burdening past information is dropped directly b y means of a generalized inversion lemma; consequently, the proposed algori thm has excellent tracking abilities and very low misjudgment. Moreover, th e scheme presented here, due to its particular structure and to the proper choice of mathematical definitions behind it, is very robust; i.e., it is l ess sensitive in the finite precision numerical error generation and propag ation. Also, the new algorithm can be parallelized via a simple technique a nd its parallel form and, when executed with four processors, is faster tha n all the already existing schemes that perform both infinite and finite wi ndow multichannel adaptive filtering. Finally, due to the particular struct ure of this scheme and to the intrinsic flexibility in the choice of the wi ndow length, the proposed algorithm can act as a full substitute of the inf inite window MRLS ones. (C) 2000 Academic Press.