作者：
Saadaoui, FouedKing Abdulaziz Univ
Fac Sci Dept Stat POB 80203 Jeddah 21589 Saudi Arabia Univ Monastir
Fac Sci Lab Algebre Theorie Nombres & Anal Nonlineaire Monastir 5019 Tunisia Univ Sousse
Inst Hautes Etud Commerciales Sahloul 3 Dist Sousse 4054 Tunisia
Various extrapolation methods have been applied to accelerate convergence of the emalgorithm. These methods are easy to implement, since they work only with em basic iterations. In other words, auxiliary quantities, ...
详细信息
Various extrapolation methods have been applied to accelerate convergence of the emalgorithm. These methods are easy to implement, since they work only with em basic iterations. In other words, auxiliary quantities, such as gradient and hessian, are not needed. In this paper, we define a new family of iterative schemes based on nonlinear extrapolation methods. It is shown that these strategies can accelerate convergence of the emalgorithm much more stably than competing methods. They are extremely general in the sense that they can accelerate any linearly convergent fixed point iterative method, and hence, any em-type algorithm. A randomly relaxed version is also deduced and numerically tested. (C) 2019 Elsevier B.V. All rights reserved.
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