Showing papers on "Recursive least squares filter published in 1968"

Iterative refinements of linear least squares solutions by Householder transformations

Abstract: An algorithm is presented in ALGOL for iteratively refining the solution to a linear least squares problem with linear constraints. Numerical results presented show that a high degree of accuracy is obtained.

A summary, by illustrations, of least-squares filters with constraints

Abstract: Several methods of combining a number of time series into a single series are discussed. They are all individual filtering followed by summation and are somewhat like Wiener filtering in that a least-squares criterion is used to design the filter coefficients. They differ from Wiener filtering in that signal information is given in the form of various constraints on the filter coefficients rather than being given as a signal correlation function. The equations are worked out explicitly for the case of two time series and three filter points and presented in such a way as to make generalization clear.

The least squares and Bubnov-Galerkin methods

Abstract: IN this paper the rate of convergence of the approximate solution, constructed by the least squares method, to the exact solution, is established subject to certain conditions. A similar problem is investigated for a generalized Bubnov-Gal'erkin method.