Fast Least Squares Algorithms in Linear Identification

The paper deals with the identification of FIR linear systems by time-domain least squares methods. Fast algorithms for solving the least squares problem are introduced, based on the notion of quasi-Toeplitz matrices. The estimation problem is solved by embedding it into a linear prediction one, and it is shown that the algorithms also allow the efficient solution of constrained least squares problems in a very common case. The iterative approach to constrained least squares identification is briefly considered, followed by the presentation of the applications considered by the authors. Finally, a few comments are made about the performances of the methods discussed.