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Classical and Discrete Differential Geometry - Theory, Applications and Algorithms (Hardcover): David Xianfeng Gu Classical and Discrete Differential Geometry - Theory, Applications and Algorithms (Hardcover)
David Xianfeng Gu; Contributions by Ruijun He; Emil Saucan; Contributions by Chang-Qing Yang
R3,417 Discovery Miles 34 170 Ships in 10 - 15 working days

This book introduces differential geometry and cutting-edge findings from the discipline by incorporating both classical approaches and modern discrete differential geometry across all facets and applications, including graphics and imaging, physics and networks. With curvature as the centerpiece, the authors present the development of differential geometry, from curves to surfaces, thence to higher dimensional manifolds; and from smooth structures to metric spaces, weighted manifolds and complexes, and to images, meshes and networks. The first part of the book is a differential geometric study of curves and surfaces in the Euclidean space, enhanced while the second part deals with higher dimensional manifolds centering on curvature by exploring the various ways of extending it to higher dimensional objects and more general structures and how to return to lower dimensional constructs. The third part focuses on computational algorithms in algebraic topology and conformal geometry, applicable for surface parameterization, shape registration and structured mesh generation. The volume will be a useful reference for students of mathematics and computer science, as well as researchers and engineering professionals who are interested in graphics and imaging, complex networks, differential geometry and curvature.

Conformal Geometry - Computational Algorithms and Engineering Applications (Paperback, Softcover reprint of the original 1st... Conformal Geometry - Computational Algorithms and Engineering Applications (Paperback, Softcover reprint of the original 1st ed. 2018)
Miao Jin, Xianfeng Gu, Ying He, Yalin Wang
R3,341 Discovery Miles 33 410 Ships in 18 - 22 working days

This book offers an essential overview of computational conformal geometry applied to fundamental problems in specific engineering fields. It introduces readers to conformal geometry theory and discusses implementation issues from an engineering perspective. The respective chapters explore fundamental problems in specific fields of application, and detail how computational conformal geometric methods can be used to solve them in a theoretically elegant and computationally efficient way. The fields covered include computer graphics, computer vision, geometric modeling, medical imaging, and wireless sensor networks. Each chapter concludes with a summary of the material covered and suggestions for further reading, and numerous illustrations and computational algorithms complement the text. The book draws on courses given by the authors at the University of Louisiana at Lafayette, the State University of New York at Stony Brook, and Tsinghua University, and will be of interest to senior undergraduates, graduates and researchers in computer science, applied mathematics, and engineering.

Conformal Geometry - Computational Algorithms and Engineering Applications (Hardcover, 1st ed. 2018): Miao Jin, Xianfeng Gu,... Conformal Geometry - Computational Algorithms and Engineering Applications (Hardcover, 1st ed. 2018)
Miao Jin, Xianfeng Gu, Ying He, Yalin Wang
R3,369 Discovery Miles 33 690 Ships in 18 - 22 working days

This book offers an essential overview of computational conformal geometry applied to fundamental problems in specific engineering fields. It introduces readers to conformal geometry theory and discusses implementation issues from an engineering perspective. The respective chapters explore fundamental problems in specific fields of application, and detail how computational conformal geometric methods can be used to solve them in a theoretically elegant and computationally efficient way. The fields covered include computer graphics, computer vision, geometric modeling, medical imaging, and wireless sensor networks. Each chapter concludes with a summary of the material covered and suggestions for further reading, and numerous illustrations and computational algorithms complement the text. The book draws on courses given by the authors at the University of Louisiana at Lafayette, the State University of New York at Stony Brook, and Tsinghua University, and will be of interest to senior undergraduates, graduates and researchers in computer science, applied mathematics, and engineering.

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