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From Approximate Variation to Pointwise Selection Principles

  • Explicit evaluation and approximation of bounded variation functionals on metric spaces
  • Highlighted feature includes a deep study of a special type of lower semicontinuous functionals
  • Accessible to upper undergraduate students taking courses in mathematical and functional analysis

Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)

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Table of contents (4 chapters)

  1. Front Matter

    Pages i-xiii
  2. The approximate variation and its properties

    • Vyacheslav V. Chistyakov
    Pages 7-23
  3. Examples of approximate variations

    • Vyacheslav V. Chistyakov
    Pages 25-43
  4. Pointwise selection principles

    • Vyacheslav V. Chistyakov
    Pages 45-79
  5. Back Matter

    Pages 81-86

About this book

The book addresses the minimization of special lower semicontinuous functionals over closed balls in metric spaces, called the approximate variation. The new notion of approximate variation contains more information about the bounded variation functional and has the following features: the infimum in the definition of approximate variation is not attained in general and the total Jordan variation of a function is obtained by a limiting procedure as a parameter tends to zero. By means of the approximate variation, we are able to characterize regulated functions in a generalized sense and provide powerful compactness tools in the topology of pointwise convergence, conventionally called pointwise selection principles.
 
The book presents a thorough, self-contained study of the approximate variation and results which were not published previously in book form. The approximate variation is illustrated by a large number of examples designed specifically for this study. The discussion elaborates on the state-of-the-art pointwise selection principles applied to functions with values in metric spaces, normed spaces, reflexive Banach spaces, and Hilbert spaces.  The highlighted feature includes a deep study of special type of lower semicontinuous functionals though the applied methods are of a general nature. The content is accessible to students with some background in real analysis, general topology, and measure theory.
 
Among the new results presented are properties of the approximate variation: semi-additivity, change of variable formula, subtle behavior with respect to uniformly and pointwise convergent sequences of functions, and the behavior on improper metric spaces. These properties are crucial for pointwise selection principles in which the key role is played by the limit superior of the approximate variation. Interestingly, pointwise selection principles may be regular, treating regulated limitfunctions, and irregular, treating highly irregular functions (e.g., Dirichlet-type functions), in which a significant role is played by Ramsey’s Theorem from formal logic.


Authors and Affiliations

  • Department of Informatics, Mathematics, and Computer Sciences, National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Vyacheslav V. Chistyakov

About the author

Vyacheslav V. Chistyakov is Professor of Mathematics at the National Research University Higher School of Economics in Nizhny Novgorod, Russia. He received a PhD in Mathematics in 1987 from the Moscow State (Lomonosov) University, Moscow, Russia, and a D.Sc. in Mathematics in 2002 from the Sobolev Institute of Mathematics (Siberian Branch of Russian Academy of Sciences), Novosibirsk, Russia. His areas of research are real and functional analysis, set-valued analysis, optimization, and the decision making theory. He authored more than 100 research articles and several books including Metric Modular Spaces: Theory and Applications, Springer, 2015.

Bibliographic Information

  • Book Title: From Approximate Variation to Pointwise Selection Principles

  • Authors: Vyacheslav V. Chistyakov

  • Series Title: SpringerBriefs in Optimization

  • DOI: https://doi.org/10.1007/978-3-030-87399-8

  • Publisher: Springer Cham

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-87398-1Published: 23 October 2021

  • eBook ISBN: 978-3-030-87399-8Published: 22 October 2021

  • Series ISSN: 2190-8354

  • Series E-ISSN: 2191-575X

  • Edition Number: 1

  • Number of Pages: XIII, 86

  • Number of Illustrations: 19 b/w illustrations

  • Topics: Optimization, Functional Analysis, Topology

Buy it now

Buying options

eBook USD 19.99 USD 39.99
50% discount Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 29.99 USD 54.99
45% discount Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access