Articoli correlati a An Introduction to Computational Stochastic PDEs: 50
Sinossi
This book offers a practical presentation of stochastic partial differential equations arising in physical applications and their numerical approximation.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sugli autori
Gabriel Lord is a Professor in the Maxwell Institute, Department of Mathematics, at Heriot-Watt University, Edinburgh. He has worked on stochastic PDEs and applications for the past ten years. He is the co-editor of Stochastic Methods in Neuroscience with C. Liang, has organised a number of international meetings in the field, and is principal investigator on the porous media processes and mathematics network funded by the Engineering and Physical Sciences Research Council (UK). He is a member of the Society for Industrial and Applied Mathematics, LMS, and EMS, as well as an Associate Editor for the SIAM Journal on Scientific Computing and the SIAM/ASA Journal on Uncertainty Quantification.
Catherine Powell is a Senior Lecturer in Applied Mathematics and Numerical Analysis at the University of Manchester. She has worked in the field of stochastic PDEs and uncertainty quantification for ten years. She has co-organised several conferences on the subject, and together with Tony Shardlow, initialised the annual NASPDE series of meetings (now in its sixth year). Currently, she is the principal investigator on an Engineering and Physical Sciences Research Council funded project on the 'Numerical Analysis of PDEs with Random Data'. She is a member of the Society for Industrial and Applied Mathematics and an Associate Editor for the SIAM/ASA Journal on Uncertainty Quantification.
Tony Shardlow has been working in the numerical analysis group at the University of Bath since 2012. Before that, he held appointments at the universities of Manchester, Durham, Oxford, and Minnesota. He completed his Ph.D. in Scientific Computing and Computational Mathematics at Stanford University in 1997.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 135,76
EUR 7,65 per la spedizione in U.S.A.
Destinazione, tempi e costi
Risultati della ricerca per An Introduction to Computational Stochastic PDEs: 50
Foto dell'editore
An Introduction to Computational Stochastic PDEs (Cambridge Texts in Applied Mathematics, Series Number 50)
Da: Best Price, Torrance, CA, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. SUPER FAST SHIPPING. Codice articolo 9780521899901
Quantità: 1 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs (Cambridge Texts in Applied Mathematics, Series Number 50)
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo ABLIING23Feb2416190021151
Quantità: Più di 20 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs (Cambridge Texts in Applied Mathematics, Series Number 50)
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9780521899901_new
Quantità: Più di 20 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs (Cambridge Texts in Applied Mathematics, Series Number 50)
Da: California Books, Miami, FL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo I-9780521899901
Quantità: Più di 20 disponibili
Foto dell'editore
Introduction to Computational Stochastic Pdes (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2014
ISBN 10: 0521899907
ISBN 13: 9780521899901
Nuovo
Rilegato
Da: Grand Eagle Retail, Mason, OH, U.S.A.
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. 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 (R) 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. This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB codes are included, so that readers can perform computations themselves and solve the test problems discussed. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780521899901
Quantità: 1 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs
Print on DemandDa: THE SAINT BOOKSTORE, Southport, Regno Unito
Valutazione del venditore 5 su 5 stelle
Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1218. Codice articolo C9780521899901
Quantità: Più di 20 disponibili
Foto dell'editore
Introduction to Computational Stochastic Pdes (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2014
ISBN 10: 0521899907
ISBN 13: 9780521899901
Nuovo
Rilegato
Da: AussieBookSeller, Truganina, VIC, Australia
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. 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 (R) 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. This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB codes are included, so that readers can perform computations themselves and solve the test problems discussed. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9780521899901
Quantità: 1 disponibili
Foto dell'editore
An Introduction to Computational Stochastic Pdes
Print on DemandDa: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: Brand New. 503 pages. 10.00x7.25x1.00 inches. In Stock. This item is printed on demand. Codice articolo __0521899907
Quantità: 1 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs
Editore:
Cambridge University Press CUP, 2014
ISBN 10: 0521899907
ISBN 13: 9780521899901
Nuovo
Rilegato
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. pp. 520. Codice articolo 2697508570
Quantità: 1 disponibili
Foto dell'editore
An Introduction to Computational Stochastic PDEs
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. pp. 520 123 Illus. (16 Col.). Codice articolo 95970053
Quantità: 1 disponibili