Series: Lecture Notes in Mathematics / Ecole D'ete de Probabilites de Saint-Flour. Num Pages: 149 pages, 12 black & white illustrations, 4 colour illustrations, biography. BIC Classification: PBKJ; PBT; PBWL. Category: (P) Professional & Vocational. Dimension: 234 x 157 x 9. Weight in Grams: 244. . 2014. 2014th Edition. Paperback. . . . .

Codice articolo V9783319043937

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Titolo: Brownian Motion and its Applications to Mathematical Analysis
Editore: Springer International Publishing AG
Data di pubblicazione: 2014
Lingua: Inglese
ISBN 10: 3319043935
ISBN 13: 9783319043937
Rilegatura: Brossura
Condizione: New

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These lecture notes provide an introduction to the applications of Brownian motion to analysis and more generally, connections between Brownian motion and analysis. Brownian motion is a well-suited model for a wide range of real random phenomena, from chaotic oscillations of microscopic objects, such as flower pollen in water, to stock market fluctuations. It is also a purely abstract mathematical tool which can be used to prove theorems in "deterministic" fields of mathematics.

The notes include a brief review of Brownian motion and a section on probabilistic proofs of classical theorems in analysis. The bulk of the notes are devoted to recent (post-1990) applications of stochastic analysis to Neumann eigenfunctions, Neumann heat kernel and the heat equation in time-dependent domains.

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These lecture notes provide an introduction to the applications of Brownian motion to analysis and, more generally, connections between Brownian motion and analysis. Brownian motion is a well-suited model for a wide range of real random phenomena, from chaotic oscillations of microscopic objects, such as flower pollen in water, to stock market fluctuations. It is also a purely abstract mathematical tool which can be used to prove theorems in "deterministic" fields of mathematics.
The notes include a brief review of Brownian motion and a section on probabilistic proofs of classical theorems in analysis. The bulk of the notes are devoted to recent (post-1990) applications of stochastic analysis to Neumann eigenfunctions, Neumann heat kernel and the heat equation in time-dependent domains.

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