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dc.contributor.author Sidi, Avram
dc.date.accessioned 2016-07-21T12:16:04Z
dc.date.available 2016-07-21T12:16:04Z
dc.date.issued 2016-07
dc.identifier.uri http://dx.doi.org/10.4236/am.2016.711111
dc.identifier.uri http://hdl.handle.net/123456789/871
dc.description.abstract An important problem that arises in different areas of science and engineering is that of computing the limits of sequences of vectors , where , N being very large. Such sequences arise, for example, in the solution of systems of linear or nonlinear equations by fixed-point iterative methods, and are simply the required solutions. In most cases of interest, however, these sequences converge to their limits extremely slowly. One practical way to make the sequences converge more quickly is to apply to them vector extrapolation methods. Two types of methods exist in the literature: polynomial type methods and epsilon algorithms. In most applications, the polynomial type methods have proved to be superior convergence accelerators. Three polynomial type methods are known, and these are the minimal polynomial extrapolation (MPE), the reduced rank extrapolation (RRE), and the modified minimal polynomial extrapolation (MMPE). In this work, we develop yet another polynomial type method, which is based on the singular value decomposition, as well as the ideas that lead to MPE. We denote this new method by SVD-MPE. We also design a numerically stable algorithm for its implementation, whose computational cost and storage requirements are minimal. Finally, we illustrate the use of SVD-MPE with numerical examples. en_US
dc.language.iso en en_US
dc.publisher Scientific Research Publishing en_US
dc.relation.ispartofseries Applied Mathematics, 2016, 7, 1260-1278;
dc.subject Vector Extrapolation en_US
dc.subject Minimal Polynomial Extrapolation en_US
dc.subject Singular Value Decomposition en_US
dc.subject Krylov Subspace Methods en_US
dc.title SVD-MPE: An SVD-Based Vector Extrapolation Method of Polynomial Type en_US
dc.type Article en_US


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