Solutions of Fixed Point Problems with Computational Errors
The book is devoted to the study of approximate solutions of fixed point problems in the presence of computational errors. It begins with a study of approximate solutions of star-shaped feasibility problems in the presence of perturbations. The goal is to show the convergence of algorithms, which ar...
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| Formato: | Recurso Electrónico livro electrónico |
| Idioma: | inglês |
| Publicado em: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edição: | 1st ed. 2024. |
| Colecção: | Springer Optimization and Its Applications,
210 |
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| Acesso em linha: | https://doi.org/10.1007/978-3-031-50879-0 |
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| 100 | 1 | |a Zaslavski, Alexander J. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Solutions of Fixed Point Problems with Computational Errors |h [electronic resource] / |c by Alexander J. Zaslavski. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (IX, 386 p.). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Use of colour is Not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background colour |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All Non-decorative content supports reading without sight |2 onix | |
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| 490 | 1 | |a Springer Optimization and Its Applications, |x 1931-6836 ; |v 210 | |
| 505 | 0 | |a 1 - Introduction -- 2 - Iterative methods in a Hilbert space -- 3 - The Cimmino algorithm in a Hilbert space -- 4 - Dynamic string-averaging methods in Hilbert spaces -- 5 - Methods with remotest set control in a Hilbert space -- 6 - Algorithms based on unions of nonexpansive maps -- 7 - Inconsistent convex feasibility problems -- 8 - Split common fixed point problems. | |
| 520 | |a The book is devoted to the study of approximate solutions of fixed point problems in the presence of computational errors. It begins with a study of approximate solutions of star-shaped feasibility problems in the presence of perturbations. The goal is to show the convergence of algorithms, which are known as important tools for solving convex feasibility problems and common fixed point problems. The text also presents studies of algorithms based on unions of nonexpansive maps, inconsistent convex feasibility problems, and split common fixed point problems. A number of algorithms are considered for solving convex feasibility problems and common fixed point problems. The book will be of interest for researchers and engineers working in optimization, numerical analysis, and fixed point theory. It also can be useful in preparation courses for graduate students. The main feature of the book which appeals specifically to this audience is the study of the influence of computational errors for several important algorithms used for nonconvex feasibility problems. | ||
| 532 | 8 | |a Accessibility summary: This PDF does Not fully comply with PDF/UA standards but does include limited screen reader support, bookmarks for easy navigation, and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognise the importance of accessibility and welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibility | |
| 532 | 8 | |a Inaccessible, or known limited accessibility | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Mathematical optimization. | |
| 650 | 0 | |a Operator theory. | |
| 650 | 0 | |a Mathematics |x Data processing. | |
| 650 | 1 | 4 | |a Optimization. |
| 650 | 2 | 4 | |a Operator Theory. |
| 650 | 2 | 4 | |a Computational Mathematics and Numerical Analysis. |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031508783 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031508806 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031508813 |
| 830 | 0 | |a Springer Optimization and Its Applications, |x 1931-6836 ; |v 210 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-50879-0 |
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| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||