ISBN: 9780521899901 - an introduction to computational stochastic pdes (cambridge texts in applied mathematics, 50, band 50) (6 Ergebnisse)

Hardcover. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

Hardcover. Zustand: Very Good. An Introduction to Computational Stochastic PDEs: 50 (Cambridge Texts in Applied Mathematics, Series Number 50) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. …

Zustand: New. In English.

Zustand: New. This book offers a practical presentation of stochastic partial differential equations arising in physical applications and their numerical approximation. Series: Cambridge Texts in Applied Mathematics. Num Pages: 516 pages, 107 b/w illus. 16 colour illus. 222 exercises. BIC Classification: PBKJ; PBWL. Category: (U) Tertiary Education (US: College). Dimension: 252 x 171 x 33. Weight in Grams: 1006. . 2014. hardcover. . . . . Books ship from the US and Ireland.…

Hardcover. Zustand: Brand New. 503 pages. 10.00x7.25x1.00 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic differential equations, and offers graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. Coverage includes traditional stochastic ODEs with white noise forcing, strong and weak approximation, and the multi-level Monte Carlo method. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo method, and introduce stochastic Galerkin finite-element methods. Finally, stochastic parabolic PDEs are developed. Assuming little previous exposure to probability and statistics, theory is developed in tandem with state-of-the-art computational methods through worked examples, exercises, theorems and proofs. The set of MATLAB® codes included (and downloadable) allows readers to perform computations themselves and solve the test problems discussed. Practical examples are drawn from finance, mathematical biology, neuroscience, fluid flow modelling and materials science.…