Produktbild: Approximate Solutions of Common Fixed-Point Problems
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Approximate Solutions of Common Fixed-Point Problems

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.05.2018

Abbildungen

IX, 454 p.

Verlag

Springer

Seitenzahl

454

Maße (L/B/H)

23,5/15,5/2,5 cm

Gewicht

698 g

Auflage

Softcover reprint of the original 1st ed. 2016

Sprache

Englisch

ISBN

978-3-319-81467-4

Beschreibung

Rezension

“The title says it all: this book is a compilation of studies of algorithms for computing approximate solutions to the problem of finding common fixed points of several operators in the presence of computational errors. … The perspective on the analysis of algorithms with fixed computational error is new, and the book is a tutorial on how to execute this analysis for dynamical string-averaging methods, which includes many classical algorithms as special cases.” (Russell Luke, Mathematical Reviews, May, 2017)






“The present book on fixed point topics focusses on the study of the convergence of iterative algorithms which are mainly intended to approximate solutions of common fixed point problems and of convex feasibility problems in the presence of computational errors. … The book, including mainly original theoretical contributions of the author to the convergence analysis of the considered iterative algorithms, is addressed to researchers interested in fixed point theory and/or convex feasibility problems.” (Vasile Berinde, zbMATH 1357.49007, 2017)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.05.2018

Abbildungen

IX, 454 p.

Verlag

Springer

Seitenzahl

454

Maße (L/B/H)

23,5/15,5/2,5 cm

Gewicht

698 g

Auflage

Softcover reprint of the original 1st ed. 2016

Sprache

Englisch

ISBN

978-3-319-81467-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Approximate Solutions of Common Fixed-Point Problems

  • 1.Introduction.- 2. Dynamic string-averaging methods in Hilbert spaces.- 3. Iterative methods in metric spaces.- 4. Dynamic string-averaging methods in normed spaces.- 5. Dynamic string-maximum methods in metric spaces.- 6. Spaces with generalized distances.- 7. Abstract version of CARP algorithm.- 8. Proximal point algorithm.- 9. Dynamic string-averaging proximal point algorithm.- 10. Convex feasibility problems.- 11. Iterative subgradient projection algorithm.- 12. Dynamic string-averaging subgradient projection algorithm.– References.– Index.