Overview
- 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.
Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 75)
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Table of contents (17 papers)
Keywords
About this book
Editors and Affiliations
Bibliographic Information
Book Title: Coping with Complexity: Model Reduction and Data Analysis
Editors: Alexander N. Gorban, Dirk Roose
Series Title: Lecture Notes in Computational Science and Engineering
DOI: https://doi.org/10.1007/978-3-642-14941-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-14940-5Published: 25 October 2010
Softcover ISBN: 978-3-642-26561-7Published: 01 December 2012
eBook ISBN: 978-3-642-14941-2Published: 21 October 2010
Series ISSN: 1439-7358
Series E-ISSN: 2197-7100
Edition Number: 1
Number of Pages: XII, 356
Number of Illustrations: 86 b/w illustrations
Topics: Computational Mathematics and Numerical Analysis, Systems Theory, Control, Theoretical, Mathematical and Computational Physics, Industrial Chemistry/Chemical Engineering