Coping with Complexity: Model Reduction and Data Analysis - neues Buch

EAN (ISBN-13): 9783642149412
ISBN (ISBN-10): 3642149413
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin
390 Seiten
Sprache: eng/Englisch

Buch in der Datenbank seit 2011-06-22T16:10:18+02:00 (Berlin)
Detailseite zuletzt geändert am 2023-11-11T16:13:06+01:00 (Berlin)
ISBN/EAN: 9783642149412

ISBN - alternative Schreibweisen:
3-642-14941-3, 978-3-642-14941-2
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: alexander roos, roo, truesdell clifford, gorb
Titel des Buches: complex analysis, complexity

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Daten vom Verlag:

Autor/in: Alexander N. Gorban; Dirk Roose
Titel: Lecture Notes in Computational Science and Engineering; Coping with Complexity: Model Reduction and Data Analysis
Verlag: Springer; Springer Berlin
356 Seiten
Erscheinungsjahr: 2010-10-21
Berlin; Heidelberg; DE
Sprache: Englisch
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XII, 356 p. 86 illus.

EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Numerische Mathematik; Verstehen; asymptotics; dimensionality reduction; invariant manifolds; kinetics; model reduction; singular perturbation; C; Computational Mathematics and Numerical Analysis; Systems Theory, Control; Theoretical, Mathematical and Computational Physics; Industrial Chemistry; Mathematics and Statistics; Kybernetik und Systemtheorie; Mathematische Physik; Industrielle Chemie und Chemietechnologie; BB

This volume contains the extended version of selected talks given at the international research workshop "Coping with Complexity: Model Reduction and Data Analysis", Ambleside, UK, August 31 – September 4, 2009. The book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.
Highly interdisciplinary and helps to circumvent the “language barriers” between different disciplines. Gives the reader an view on the state-of-the-art in both theoretical and practical issues in model reduction and data analysis of complex and multiscale mathematical models.