Trust-region and other regularisations of linear least-squares problems

We consider methods for regularising the least-squares solution of the linear system Ax=b. In particular, we propose iterative methods for solving large problems in which a trust-region bound ‖x‖≤Δ is imposed on the size of the solution, and in which the least value of linear combinations of ‖Ax−b‖2q and a regularisation term ‖x‖2p for various p and q=1,2 is sought. In each case, one or more “secular” equations are derived, and fast Newton-like solution procedures are suggested. The resulting algorithms are available as part of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathsf{G}$\end{document} ALAHAD optimization library.