Projection-minimization methods for nonsymmetric linear systems Original Research Article

We consider projection-minimization methods for solving systems of linear equations. We transform these methods to new ones and show that they converge faster, in some sense. We present, in particular, the transform of the norm decomposition method of Gastinel. The new algorithm presents advantages over some known conjugate-gradient-like methods. This new method is studied, and numerical examples are given.