Fractional Differential Equations: An Approach via Fractional Derivatives: 206 - Rilegato

Jin, Bangti

Rilegato

ISBN 10: 3030760421 ISBN 13: 9783030760427

Casa editrice: Springer Nature, 2021

Riassunto

This graduate textbook provides a self-contained introduction to modern mathematical theory on fractional differential equations. It addresses both ordinary and partial differential equations with a focus on detailed solution theory, especially regularity theory under realistic assumptions on the problem data. The text includes an extensive bibliography, application-driven modeling, extensive exercises, and graphic illustrations throughout to complement its comprehensive presentation of the field. It is recommended for graduate students and researchers in applied and computational mathematics, particularly applied analysis, numerical analysis and inverse problems.

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Informazioni sull'autore

Bangti Jin received the B.Eng. degree in polymeric materials and engineering in 2002, the

M.Sc. degree in computational mathematics in 2005, both from Zhejiang University, Hangzhou, China, and the Ph.D. degree in applied mathematics from the Chinese University of Hong Kong, Hong Kong, in 2008. Previously, he was an Assistant Professor of mathematics at the University of California, Riverside (2013–2014), a Visiting Assistant Professor at Texas A&M University (2010–2013), an Alexandre von Humboldt Postdoctoral Researcher at the University of Bremen (2009–2010). He is currently Professor of Inverse Problems at the Department of Computer Science, University College London, London, U.K. His research interests include computational inverse problems and numerical analysis of differential equations.

Dalla quarta di copertina

This graduate textbook provides a self-contained introduction to modern mathematical theory on fractional differential equations. It addresses both ordinary and partial differential equations with a focus on detailed solution theory, especially regularity theory under realistic assumptions on the problem data. The text includes an extensive bibliography, application-driven modeling, extensive exercises, and graphic illustrations throughout to complement its comprehensive presentation of the field. It is recommended for graduate students and researchers in applied and computational mathematics, particularly applied analysis, numerical analysis and inverse problems.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 3030760421
• ISBN 13: 9783030760427
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 368
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania