Let T be a bounded linear operator between two Hilbert spaces with the range of T not necessarily closed, and let T † denote the generalized inverse of T. The method of steepest descent for minimizing is shown to converge monotonically starting with x 0 = 0, to T † y for any y whose orthogonal projection on the closure of the range of T, is in the range of TT *. This set of y's is dense in the domain of T†. The method is also applied to generalized least squares solutions of a class of unbounded linear operator equations
No takes yet. Share an insight, caveat, or question.
Kammerer et al. (1971) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: