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Integration on Infinite-Dimensional Surfaces and Its Applications

  • A. V. Uglanov

Part of the Mathematics and Its Applications book series (MAIA, volume 496)

Table of contents

  1. Front Matter
    Pages i-ix
  2. A. V. Uglanov
    Pages 1-8
  3. A. V. Uglanov
    Pages 9-10
  4. A. V. Uglanov
    Pages 11-40
  5. A. V. Uglanov
    Pages 41-132
  6. A. V. Uglanov
    Pages 133-244
  7. Back Matter
    Pages 245-272

About this book

Introduction

It seems hard to believe, but mathematicians were not interested in integration problems on infinite-dimensional nonlinear structures up to 70s of our century. At least the author is not aware of any publication concerning this theme, although as early as 1967 L. Gross mentioned that the analysis on infinite­ dimensional manifolds is a field of research with rather rich opportunities in his classical work [2. This prediction was brilliantly confirmed afterwards, but we shall return to this later on. In those days the integration theory in infinite­ dimensional linear spaces was essentially developed in the heuristic works of RP. Feynman [1], I. M. Gelfand, A. M. Yaglom [1]). The articles of J. Eells [1], J. Eells and K. D. Elworthy [1], H. -H. Kuo [1], V. Goodman [1], where the contraction of a Gaussian measure on a hypersurface, in particular, was built and the divergence theorem (the Gauss-Ostrogradskii formula) was proved, appeared only in the beginning of the 70s. In this case a Gaussian specificity was essential and it was even pointed out in a later monograph of H. -H. Kuo [3] that the surface measure for the non-Gaussian case construction problem is not simple and has not yet been solved. A. V. Skorokhod [1] and the author [6,10] offered different approaches to such a construction. Some other approaches were offered later by Yu. L. Daletskii and B. D. Maryanin [1], O. G. Smolyanov [6], N. V.

Keywords

Boundary value problem Hilbert space Probability theory Stochastic processes Variance distribution functional analysis mathematical physics partial differential equation stochastic process

Authors and affiliations

  • A. V. Uglanov
    • 1
  1. 1.Yaroslavl State UniversityYaroslavlRussia

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-9622-0
  • Copyright Information Springer Science+Business Media B.V. 2000
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-5384-8
  • Online ISBN 978-94-015-9622-0
  • Buy this book on publisher's site
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