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eBook Random Series and Stochastic Integrals: Single and Multiple (Probability and Its Applications) epub

by Stanislaw Kwapien,Wojbor A. Woyczynski

eBook Random Series and Stochastic Integrals: Single and Multiple (Probability and Its Applications) epub
  • ISBN: 081764198X
  • Author: Stanislaw Kwapien,Wojbor A. Woyczynski
  • Genre: Engineering
  • Subcategory: Engineering
  • Language: English
  • Publisher: Birkhäuser; 1st ed. 1992. 2nd printing 2000 edition (May 11, 2000)
  • Pages: 376 pages
  • ePUB size: 1825 kb
  • FB2 size 1145 kb
  • Formats lrf azw doc mbr


This book studies the foundations of the theory of linear and nonlinear forms in single and multiple random variables including the single and multiple random series and stochastic integrals, both Gaussian and non-Gaussian. This subject is intimately connected with a number of classical problems of probability theory such as the summation of independent random variables, martingale theory, and Wiener's theory of polynomial chaos. The book contains a number of older results as well as more recent, or previously unpublished, results.

Fourier Series and Integrals focuses on the extraordinary power and flexibility of Fourier s basic series and integrals and on the astonishing variety

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In book: Chaos Expansions, Multiple Wiener Itô Integrals and Their Applications, Publisher: CRC . Random series and stochastic integrals: Single and multiple. Wojbor A. Woyczynski.

Cite this publication. A zero-one dichotomy theorem for r-semi-stable laws on infinite dimensional linear spaces.

This book studies the foundations of the theory of linear and nonlinear forms in single and multiple random variables including single and multiple random series and stochastic integrals, both Gaussian and non-Gaussian

Souganidis, . Stochastic homogenization of Hamilton-Jacobi equations and some applications.

Probability and its Applications. Birkhäuser, Boston, MA, 1992. Souganidis, . 20 (1999), no. 1, 1-11. Szulga, . Multiple stochastic integrals with respect to symmetric infinitely divisible random measures. 19 (1991), 1145-1156.

This book fills a large gap in random sets, which is perhaps the most underutilized field of mathematics, in. .Just the basics of probability theory and measure theory are needed to understand and work through the book.

This book fills a large gap in random sets, which is perhaps the most underutilized field of mathematics, in terms of comparing its power and it potential in applications. This book is good enough and solid enough to fill this need, and it might therefore allow serious applications to go forward. Very highly recommended.

Random series and stochastic integrals: Single and multiple. Probability and its Applications. Boston, MA: Birkhäuser Boston, Inc. pp. xvi+360. Sen (1992) p. 307. ^ Sen (1992), p306. Borovskikh's last chapter discusses U-statistics for exchangeable random elements taking values in a vector space (separable Banach space).

Woyczyński, Random Series and Stochastic Integrals: Single and Multiple. Birkhäuser, Boston (1992). Latala, . Tail and moment estimates for sums of independent random vectors with logarithmically concave tails. M. Ledoux and M. Talagrand, Probability in Banach Spaces. Springer-Verlag, New York (1991). Ledoux, The Concentration of Measure Phenomenon.

This book studies the foundations of the theory of linear and nonlinear forms in single and multiple random variables including the single and multiple random series and stochastic integrals, both Gaussian and non-Gaussian. This subject is intimately connected with a number of classical problems of probability theory such as the summation of independent random variables, martingale theory, and Wiener's theory of polynomial chaos. The book contains a number of older results as well as more recent, or previously unpublished, results. The emphasis is on domination principles for comparison of different sequences of random variables and on decoupling techniques. These tools prove very useful in many areas ofprobability and analysis, and the book contains only their selected applications. On the other hand, the use of the Fourier transform - another classical, but limiting, tool in probability theory - has been practically eliminated. The book is addressed to researchers and graduate students in prob­ ability theory, stochastic processes and theoretical statistics, as well as in several areas oftheoretical physics and engineering. Although the ex­ position is conducted - as much as is possible - for random variables with values in general Banach spaces, we strive to avoid methods that would depend on the intricate geometric properties of normed spaces. As a result, it is possible to read the book in its entirety assuming that all the Banach spaces are simply finite dimensional Euclidean spaces.
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