In this paper, a successive low-rank matrix approximation algorithm is presented for the completion (MC) based on hard thresholding method, which approximate optimal from rank-one step by step. The enables distance between with observed elements and projection manifold to be minimum. obtained when zero. theory, convergence convergent error of new are analyzed in detail. Furthermore, some numeri...

Convex relaxations of the power flow equations and, in particular, the Semi-Definite Programming (SDP) and SecondOrder Cone (SOC) relaxations, have attracted significant interest in recent years. The Quadratic Convex (QC) relaxation is a departure from these relaxations in the sense that it imposes constraints to preserve stronger links between the voltage variables through convex envelopes of ...

The vast majority of recent advances in the field of numerical radiative transfer relies on approximate operator methods better known in astrophysics as Accelerated Lambda-Iteration (ALI). A superior class of iterative schemes, in term of rates of convergence, such as Gauss-Seidel and Successive Overrelaxation methods were therefore quite naturally introduced in the field of radiative transfer ...

Convergence of the iterative method based on the successive overrelaxation (SOR) method is investigated to solve the matrix equation in the moment analysis of array antennas. It is found this method can be applied to the sub domain method of moments with fast convergence if the grouping technique is applied and the over-relaxation parameter is properly selected, and the computation time for sol...

In the Tree Augmentation problem we are given a tree T = (V, F ) and an additional set E ⊆ V × V of edges, called “links”, with positive integer costs {ce : e ∈ E}. The goal is to augment T by a minimum cost set of links J ⊆ E such that T ∪ J is 2-edge-connected. Let M denote the maximum cost of a link. Recently, Adjiashvili [1] introduced a novel LP for the problem and used it to break the nat...