New generalized least squares estimation algorithm for system identification

This paper presents modified formulations of the generalized least squares estimation algorithm for system parameter identification. Two sets of results are derived: First the existing algorithm is reformulated by eliminating the intermediate filtering procedures and introducing the system´s input-output correlation matrices. Then it is shown that the new algorithm can be conveniently simplified to a form which does not require repeated matrix inversions.