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Computing
Article . 1991 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1991
Data sources: zbMATH Open
DBLP
Article . 2020
Data sources: DBLP
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Orders of convergence for superlineary convergent chaotic iterations

Orders of convergence for superlinearly convergent chaotic iterations
Authors: Frommer, Andreas;

Orders of convergence for superlineary convergent chaotic iterations

Abstract

If on computers with multiprocessors individual processors are allowed to proceed without waiting for each other it is natural to consider so- called chaotic iterations for computations on such computers. The author proves a theorem giving conditions for superlinear convergence of chaotic iterations in an appropriate setting. The theorem also contains a statement on the \(R\)-order of the sequence generated. The author remarks that the new theorem can be regarded as giving a relationship between the speed of convergence of the total step or Gauss- Jacobi method for a given (in general nonlinear) mapping and chaotic iteration methods.

Country
Germany
Related Organizations
Keywords

ddc:510, Numerical solutions to equations with nonlinear operators, multiprocessors, Parallel numerical computation, chaotic iterations, Gauss-Jacobi method, 510, Iterative procedures involving nonlinear operators, superlinear convergence, \(R\)-order, Mathematics, info:eu-repo/classification/ddc/510

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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