Recursive least-squares algorithms of modified Gram-Schmidt type for parallel weight extraction
Hideaki Sakai · IEEE Transactions on Signal Processing · 1994
This paper presents some new algorithms for parallel weight extraction in the recursive least-squares (RLS) estimation based on the modified Gram-Schmidt (MGS) method. These are the counterparts of the algorithms using an inverse QR decomposition based on the Givens rotations and do not contain the square root operation. Systolic-array implementations of the algorithms are considered on a 2-D rhombic array. Simulation results are also presented to compare the finite word-length effect of these new algorithms and existing algorithms.>