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Hiriart-Urruty, Jean-Baptiste; Lemarechal, Claude - Convex Analysis and Minimization Algorithms - 9783540568506 - V9783540568506
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Convex Analysis and Minimization Algorithms

€ 182.28
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Description for Convex Analysis and Minimization Algorithms Hardback. This book covers the fundamentals of convex analysis, a refinement of standard calculus with equalities and approximations replaced by inequalities. Reviews minimization algorithms, which provide immediate application to optimization and operations research. Series: Die Grundlehren der Mathematischen Wissenschaften. Num Pages: 436 pages, biography. BIC Classification: PBKQ; PBW. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 25. Weight in Grams: 796.
Convex Analysis may be considered as a refinement of standard calculus, with equalities and approximations replaced by inequalities. As such, it can easily be integrated into a graduate study curriculum. Minimization algorithms, more specifically those adapted to non-differentiable functions, provide an immediate application of convex analysis to various fields related to optimization and operations research. These two topics making up the title of the book, reflect the two origins of the authors, who belong respectively to the academic world and to that of applications. Part I can be used as an introductory textbook (as a basis for courses, or for ... Read more

Product Details

Format
Hardback
Publication date
1993
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
436
Condition
New
Series
Die Grundlehren der Mathematischen Wissenschaften
Number of Pages
418
Place of Publication
Berlin, Germany
ISBN
9783540568506
SKU
V9783540568506
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Convex Analysis and Minimization Algorithms
From the reviews: "... The book is very well written, nicely illustrated, and clearly understandable even for senior undergraduate students of mathematics... Throughout the book, the authors carefully follow the recommendation by A. Einstein: 'Everything should be made as simple as possible, but not simpler.'"

Goodreads reviews for Convex Analysis and Minimization Algorithms


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