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Riemannian Geometry (Lecture Notes in Artificial Intelligence)
 
 
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Riemannian Geometry (Lecture Notes in Artificial Intelligence) [Paperback]

S. Gallot (Author), Dominique Hulin (Author), Sylvestre Gallot (Author), Jacques Lafontaine (Author)
4.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

December 1990 3540524010 978-3540524014
This book, based on a graduate course on Riemannian geometryand analysis onmanifolds, given in Paris, covers the topicsof differential manifolds, Riemannian metrics, connections,geodesics and curvature, with special emphasis on theintrinsic features on the subject.Classical results on the relations between curvature andtopology are treated in detail. The bookis quiteself-contained, assuming of the reader only a knowledge ofdifferential calculus in Euclidean space. It containsnumerous exercises with full solutions and a series ofdetailed examples which are picked up again repeatedly toillustrate each new definition or property introduced.This book addresses both the graduate student wanting tolearn Riemannian geometry, and also the professionalmathematician from a neighbouring field who needsinformation about ideas and techniques which are nowpervading many parts of mathematics.

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Editorial Reviews

Review

P. Petersen

Riemannian Geometry

"A nice introduction to Riemannian geometry, containing basic theory as well as several advanced topics."

—EUROPEAN MATHEMATICAL SOCIETY

--This text refers to the Hardcover edition.

Product Details

  • Paperback: 284 pages
  • Publisher: Springer (December 1990)
  • Language: English
  • ISBN-10: 3540524010
  • ISBN-13: 978-3540524014
  • Shipping Information: View shipping rates and policies
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #7,779,019 in Books (See Top 100 in Books)

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4 of 12 people found the following review helpful:
4.0 out of 5 stars Hard to say, February 9, 2008
This was the official 100% recommended, guaranteed text for my Riemannian Geometry class. Supplementing this book with do Carmo's text, I was able to get something out of the class, but I think rereading both of them now would be much better. The condensed one chapter course on manifolds at the beginning of GHL wasn't sufficient to learn/relearn everything I needed to know in order to read it for the first time.
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Inside This Book (learn more)
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First Sentence:
1.1 Definition. A subset M Rn+k is an n-dimensional submanifold of class Cp of Rn+k if, for any x M, there exists a neighborhood U of x in Rn+k and a Cp submersion f : U Rk such that U M = f-1(0) (we recall that f is a submersion if its differential map is surjective at each point). Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
orientation atlas, isoperimetric profile, strictly positive sectional curvature, acceleration vector field, hyperboloid model, isotropy irreducible, flat tori, isotropy representation, second variation formula, geodesic spray, minimal geodesic, first variation formula, claimed formula, local isometry, unit normal vector field, covering map, coordinate vector fields, isometry group, unit tangent bundle, minimizing geodesic, standard sphere, parallel vector field, injectivity radius, revolution surface, map exp
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Anti de Sitter, Elie Cartan, G-invariant Riemannian
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