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Reformulation of the Anderson method using singular value decomposition for stable convergence in self-consistent calculations
2009
JSIAM Letters
The Anderson method provides a significant acceleration of convergence in solving nonlinear simultaneous equations by trying to minimize the residual norm in a least-square sense at each iteration step. In the present study I use singular value decomposition to reformulate the Anderson method. The proposed version contains only a single parameter which should be determined in a trial-and-error way, whereas the original one contains two. This reduction leads to stable convergence in real-world
doi:10.14495/jsiaml.1.32
fatcat:msa2pq3yvbgu7npl4gr7gr276e