A generalized successive overrelaxation method for least squares problems. (English) Zbl 0907.65043

A new iterative method (called generalized successive overrelaxation) is given for solving large sparse least squares problems and computing the minimum norm solution to underdetermined consistent linear systems. The method is convergent if the matrix has full column rank. The method involves a matrix \(P\) as a preconditioner and a parameter \(\rho\) as an accelerator parameter. By suitable choosing of matrix \(P\) parallel computations are possible.


65F20 Numerical solutions to overdetermined systems, pseudoinverses
65F35 Numerical computation of matrix norms, conditioning, scaling
65F10 Iterative numerical methods for linear systems
65F50 Computational methods for sparse matrices
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