Acceleration of Convergence of Vector Sequences
Author(s) -
Avram Sidi,
William F. Ford,
David A. Smith
Publication year - 1986
Publication title -
siam journal on numerical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.78
H-Index - 134
eISSN - 1095-7170
pISSN - 0036-1429
DOI - 10.1137/0723013
Subject(s) - extrapolation , mathematics , convergence (economics) , acceleration , stability (learning theory) , rank (graph theory) , polynomial , numerical analysis , numerical stability , algorithm , mathematical analysis , computer science , combinatorics , physics , classical mechanics , machine learning , economics , economic growth
A general approach to the construction of convergence acceleration methods for vector sequences is proposed. Using this approach, one can generate some known methods, such as the minimal polynomial extrapolation, the reduced rank extrapolation, and the topological epsilon algorithm, and also some new ones. Some of the new methods are easier to implement than the known methods and are observed to have similar numerical properties. The convergence analysis of these new methods is carried out, and it is shown that they are especially suitable for accelerating the convergence of vector sequences that are obtained when one solves linear systems of equations iteratively. A stability analysis is also given, and numerical examples are provided. The convergence and stability properties of the topological epsilon algorithm are likewise given.
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