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Convolution-like Structures, Differential Operators and Diffusion Processes / by Rúben Sousa, Manuel Guerra, Semyon Yakubovich
(Lecture Notes in Mathematics. ISSN:16179692 ; 2315)

1st ed. 2022.
出版者 Cham : Springer International Publishing : Imprint: Springer
出版年 2022
本文言語 英語
大きさ XII, 262 p. 1 illus. in color : online resource
冊子体 Convolution-like structures, differential operators and diffusion processes / Rúben Sousa, Manuel Guerra, Semyon Yakubovich ; : pbk
著者標目 *Sousa, Rúben author
Guerra, Manuel author
Yakubovich, Semyon author
SpringerLink (Online service)
件 名 LCSH:Probabilities
LCSH:Operator theory
LCSH:Special functions
LCSH:Mathematical analysis
FREE:Probability Theory
FREE:Operator Theory
FREE:Special Functions
FREE:Integral Transforms and Operational Calculus
一般注記 This book provides an introduction to recent developments in the theory of generalized harmonic analysis and its applications. It is well known that convolutions, differential operators and diffusion processes are interconnected: the ordinary convolution commutes with the Laplacian, and the law of Brownian motion has a convolution semigroup property with respect to the ordinary convolution. Seeking to generalize this useful connection, and also motivated by its probabilistic applications, the book focuses on the following question: given a diffusion process Xt on a metric space E, can we construct a convolution-like operator * on the space of probability measures on E with respect to which the law of Xt has the *-convolution semigroup property? A detailed analysis highlights the connection between the construction of convolution-like structures and disciplines such as stochastic processes, ordinary and partial differential equations, spectral theory,special functions and integral transforms. The book will be valuable for graduate students and researchers interested in the intersections between harmonic analysis, probability theory and differential equations
HTTP:URL=https://doi.org/10.1007/978-3-031-05296-5
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Springer eBooks 9783031052965
電子リソース
EB00251298

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データ種別 電子ブック
分 類 LCC:QA273.A1-274.9
DC23:519.2
書誌ID 4000339784
ISBN 9783031052965

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