The Geometry of Domains in Space (Birkhäuser Advanced Texts / Basler Lehrbücher)

The Geometry of Domains in Space (Birkhäuser Advanced Texts / Basler Lehrbücher) pdf epub mobi txt 电子书 下载 2025

出版者:Birkhäuser Boston
作者:Steven G. Krantz
出品人:
页数:319
译者:
出版时间:1999-05-01
价格:USD 84.95
装帧:Hardcover
isbn号码:9780817640972
丛书系列:Birkhäuser Advanced Texts Basler Lehrbücher
图书标签:
  • 几何分析 
  • 几何 
  • Geometry 
  • Geometrical_Analysis 
  •  
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Traditionally, analysis on Euclidean space is based on the study of the classical groups that act on the space. The classical treatises focus on rotations, dilations, and especially translations; all of these tools and techniques have shaped the way in which classical analysis on Euclidean space has developed.

On the other hand, a modern analytical treatment, such as the one presented here, often focuses on domains in space. A domain is the natural venue for various problems arising from physics, as well as the natural setting for the study of boundary value problems. Instead of considering group actions (inappropriate since a typical domain has on natural symmetries), one considers properties that arise from the intrinsic geometry of the domain and from the geometry of the boundary as a codimension one manifold in space.

Contributing to part of the new "toolkit" that should be at hand for every analyst, the authors cover a wide array of topics: imbedded manifolds, curvature, positive reach, Sard's theorem, Sobolev spaces, the isoperimetric inequality, Weyl's theorem, covering theorems, convex functions, and Stokes's theorem in all of its many formulations, to name just several. All geometric ideas are treated in a self-contained manner.

This comprehensive treatment of domains (in space) emphasizes the growing interaction between analysis and geometry. Geometric analysis, as it is known, is currently an important area of study for both pure and applied mathematicians, physicists, and engineers. Aimed at graduate students of the field, this monograph will be useful in the classroom or as a resource for self-study. The prerequisites are minimal; a good understanding of multivariate calculus and linear algebra will suffice for most purposes.

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