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Convex Analysis: (PMS-28) [Pehme köide]

  • Formaat: Paperback / softback, 470 pages, kõrgus x laius: 229x152 mm, kaal: 595 g
  • Sari: Princeton Mathematical Series
  • Ilmumisaeg: 12-Jan-1997
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691015864
  • ISBN-13: 9780691015866
Teised raamatud teemal:
  • Formaat: Paperback / softback, 470 pages, kõrgus x laius: 229x152 mm, kaal: 595 g
  • Sari: Princeton Mathematical Series
  • Ilmumisaeg: 12-Jan-1997
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691015864
  • ISBN-13: 9780691015866
Teised raamatud teemal:
Available for the first time in paperback, R. Tyrrell Rockafellar's classic study presents readers with a coherent branch of nonlinear mathematical analysis that is especially suited to the study of optimization problems. Rockafellar's theory differs from classical analysis in that differentiability assumptions are replaced by convexity assumptions. The topics treated in this volume include: systems of inequalities, the minimum or maximum of a convex function over a convex set, Lagrange multipliers, minimax theorems and duality, as well as basic results about the structure of convex sets and the continuity and differentiability of convex functions and saddle- functions. This book has firmly established a new and vital area not only for pure mathematics but also for applications to economics and engineering. A sound knowledge of linear algebra and introductory real analysis should provide readers with sufficient background for this book. There is also a guide for the reader who may be using the book as an introduction, indicating which parts are essential and which may be skipped on a first reading.

Arvustused

"This book should remain for some years as the standard reference for anyone interested in convex analysis."--J. D. Pryce, Edinburgh Mathematical Society

Preface vii(4)
Introductory Remarks: a Guide for the Reader xi
PART I: BASIC CONCEPTS 3(40)
1. Affine Sets
3(7)
2. Convex Sets and Cones
10(6)
3. The Algebra of Convex Sets
16(7)
4. Convex Functions
23(9)
5. Functional Operations
32(11)
PART II: TOPOLOGICAL PROPERTIES 43(52)
6. Relative Interiors of Convex Sets
43(8)
7. Closures of Convex Functions
51(9)
8. Recession Cones and Unboundedness
60(12)
9. Some Closedness Criteria
72(10)
10. Continuity of Convex Functions
82(13)
PART III: DUALITY CORRESPONDENCES 95(58)
11. Separation Theorems
95(7)
12. Conjugates of Convex Functions
102(10)
13. Support Functions
112(9)
14. Polars of Convex Sets
121(7)
15. Polars of Convex Functions
128(12)
16. Dual Operations
140(13)
PART IV: REPRESENTATION AND INEQUALITIES 153(60)
17. Caratheodory's Theorem
153(9)
18. Extreme Points and Faces of Convex Sets
162(8)
19. Polyhedral Convex Sets and Functions
170(9)
20. Some Applications of Polyhedral Convexity
179(6)
21. Helly's Theorem and Systems of Inequalities
185(13)
22. Linear Inequalities
198(15)
PART V: DIFFERENTIAL THEORY 213(50)
23. Directional Derivatives and Subgradients
213(14)
24. Differntial Continuity and Monotonicity
227(14)
25. Differentiability of Convex Functions
241(10)
26. The Legendre Transformation
251(12)
PART VI: CONTRAINED EXTREMUM PROBLEMS 263(86)
27. The Minimum of a Convex Function
263(10)
28. Ordinary Convex Programs and Legrange Multipliers
273(18)
29. Bifunctions and Generalized Convex Programs
291(16)
30. Adjoint Bifunctions and Dual Programs
307(20)
31. Fenchel's Duality Theorem
327(15)
32. The Maximum of a Convex Function
342(7)
PART VII: SADDLE-FUNCTIONS AND MINIMAX THEORY 349(52)
33. Saddle-Functions
349(10)
34. Closures and Equivalence Classes
359(11)
35. Continuity and Differentiability of Saddle-functions
370(9)
36. Minimax Problems
379(9)
37. Conjugate Saddle-functions and Minimax Theorems
388(13)
PART VIII: CONVEX ALGEBRA 401(24)
38. The Algebra of Bifunctions
401(12)
39. Convex Processes
413(12)
Comments and References 425(8)
Bibliography 433(14)
Index 447


R. Tyrrell Rockafellar is Professor of Mathematics and Applied Mathematics at the University of Washington-Seattle. For his work in convex analysis and optimization, he was awarded the Dantzig Prize by the Society for Industrial and Applied Mathematics and the Mathematical Programming Society.