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Differential Geometry and Lie Groups

Media-Kombination
XXIX, 1397 Seiten
2022 | 1st ed.
Springer International Publishing
978-3-031-20629-0 (ISBN)
106,99 inkl. MwSt
This textbook set offers both an introduction to differential geometry designed for readers interested in modern geometry processing, as well as an exploration of more advanced topics. In the first volume, the authors work from basic undergraduate prerequisites to develop manifold theory and Lie groups from scratch; fundamental topics in Riemannian geometry follow, culminating in the theory that underpins manifold optimization techniques. Students and professionals working in computer vision, robotics, and machine learning will appreciate this pathway into the mathematical concepts behind many modern applications. The second volume then uses analytic and algebraic perspectives to augment core topics, with the authors taking care to motivate each new concept. Whether working toward theoretical or applied questions, readers will appreciate this accessible exploration of the mathematical concepts behind many modern applications.
The first volume, Differential Geometry and Lie Groups: A Computational Perspective, offers a uniquely accessible perspective on differential geometry for those interested in the theory behind modern computing applications. Equally suited to classroom use or independent study, the text will appeal to students and professionals alike; only a background in calculus and linear algebra is assumed.
Volume two, Differential Geometry and Lie Groups: A Second Course, captures the mathematical theory needed for advanced study in differential geometry with a view to furthering geometry processing capabilities. As with the first, this volume is suitable for both classroom use and independent study.

lt;p>Jean Gallier is Professor of Computer and Information Science at the University of Pennsylvania, Philadelphia. His research interests include geometry and its applications, geometric modeling, and differential geometry. He is also a member of the University of Pennsylvania's Department of Mathematics, and its Center for Human Modelling and Simulation.

Jocelyn Quaintance is postdoctoral researcher at the University of Pennsylvania who has contributed to the fields of combinatorial identities and power product expansions. Her recent mathematical books investigate the interplay between mathematics and computer science. Covering areas as diverse as differential geometry, linear algebra, optimization theory, and Fourier analysis, her writing illuminates the mathematics behind topics relevant to engineering, computer vision, and robotics.

Erscheint lt. Verlag 27.9.2022
Zusatzinfo XXIX, 1397 p. 143 illus., 64 illus. in color. 2 volume-set.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Geometrie / Topologie
Schlagworte adjoint representation • Construction of manifolds from gluing data • differential geometry for computer vision • Differential geometry for computing • differential geometry for geometry processing • differential geometry for machine learning • differential geometry for robotics • differential geometry textbook • grassmannian manifold • homogeneous spaces • lie algebras for computing • Lie Brackets • linear lie groups • Lorentz groups • matrix exponential • matrix Lie groups • Riemannian manifold curvature • Riemann manifold • stiefel manifold • Theory of manifold optimization techniques
ISBN-10 3-031-20629-0 / 3031206290
ISBN-13 978-3-031-20629-0 / 9783031206290
Zustand Neuware
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