Handbook of Variational Methods for Nonlinear Geometric Data (PDF)
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This book explains how variational methods have evolved to being amongst the most powerful tools for applied mathematics. They involve techniques from various branches of mathematics such as statistics, modeling, optimization, numerical mathematics and analysis. The vast majority of research on variational methods, however, is focused on data in linear spaces. Variational methods for non-linear data is currently an emerging research topic.
As a result, and since such methods involve various branches of mathematics, there is a plethora of different, recent approaches dealing with different aspects of variational methods for nonlinear geometric data. Research results are rather scattered and appear in journals of different mathematical communities.
The main purpose of the book is to account for that by providing, for the first time, a comprehensive collection of different research directions and existing approaches in this context. It is organizedin a way that leading researchers from the different fields provide an introductory overview of recent research directions in their respective discipline. As such, the book is a unique reference work for both newcomers in the field of variational methods for non-linear geometric data, as well as for established experts that aim at to exploit new research directions or collaborations.
Martin Holler was born on May 21, 1986 in Austria. He received his MSc (2010) and his PhD (2013) with a "promotio sub auspiciis praesidentis rei publicae" in Mathematics from the University of Graz. After research stays at the University of Cambridge, UK, and the Ecole Polytechnique, Paris, he currently holds a University Assistant position at the Institute of Mathematics and Scientific Computing of the University of Graz. His research interests include inverse problems and mathematical image processing, in particular the development and analysis of mathematical models in this context as well as applications in biomedical imaging, image compression and beyond.
Andreas Weinmann was born on July 18, 1979 in Augsburg, Germany. He studied mathematics with minor in computer science at TU Munich, and received his Diploma degree in mathematics and computer science from TU Munich in 2006 (with highest distinction). He was assistant at the Institute of Geometry, TU Graz. He obtained his Ph.D. degree from TU Graz in 2010 (with highest distinction). Thenhe worked as a researcher
- 2020, 1st ed. 2020, 701 Seiten, Englisch
- Herausgegeben: Philipp Grohs, Martin Holler, Andreas Weinmann
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030313514
- ISBN-13: 9783030313517
- Erscheinungsdatum: 03.04.2020
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- Dateiformat: PDF
- Größe: 26 MB
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