96,95 €
96,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
48 °P sammeln
96,95 €
96,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
48 °P sammeln
Als Download kaufen
96,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
48 °P sammeln
Jetzt verschenken
96,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
48 °P sammeln
  • Format: PDF

Includes both theoretical and computational exercises, allowing for use with mixed-level classes Provides Matlab codes for examples The first book to emphasizes the Wong-Zakai approximation Offers an approach to stochastic modeling other than the common Monte Carlo methods

Produktbeschreibung
Includes both theoretical and computational exercises, allowing for use with mixed-level classes
Provides Matlab codes for examples
The first book to emphasizes the Wong-Zakai approximation
Offers an approach to stochastic modeling other than the common Monte Carlo methods

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Rezensionen
"Zhang and Karniadakis' book may be used as a textbook, but it may also be considered as a reference for the state of the art concerning the numerical solution of stochastic differential equations involving white noise/Wiener processes/ Brownian motion. ... Bibliographic notes address the state of the art in the field. Appendices give the necessary background in probability, stochastic calculus, semi-analytical approximation methods for stochastics differential equation, Gauss quadrature ... . " (José Eduardo Souze de Cursi, Mathematical Reviews, September, 2018)

"It is an interesting book on numerical methods for stochastic partial differential equations with white noise through the framework of Wong-Zakai approximation. ... . It is to be noted that the authors provide a thorough review of topics both theoretical and computational exercises to justify the effectiveness of the developed methods. Further, the MATLAB files are made available to the researchers and readers to understand the state of art of numerical methods for stochastic partial differential equations." (Prabhat Kumar Mahanti, zbMATH 1380.65021, 2018)