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Convex Optimization in Normed Spaces: Theory, Methods and Examples: SpringerBriefs in Optimization

Autor Juan Peypouquet
en Limba Engleză Paperback – 30 mar 2015
This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.
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Specificații

ISBN-13: 9783319137094
ISBN-10: 3319137093
Pagini: 122
Ilustrații: XIV, 124 p. 17 illus.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 2.23 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Optimization

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Basic Functional Analysis.- Existence of Minimizers.- Convex Analysis and Subdifferential Calculus.- Examples.- Problem-solving Strategies.- Keynote Iterative Methods.

Recenzii

“This short book is dedicated to convex optimization, beginning with theoretical aspects, ending with numerical methods, and complemented with numerous examples. … this is an interesting and well-written book that is adequate for a graduate-level course on convex optimization.” (Constantin Zălinescu, Mathematical Reviews, November, 2015)

Notă biografică

Juan Peypouquet is an Associate Professor at the Mathematics Department of the Universidad Tecnica Federico Santa Maria.  His main research interest is the study of the asymptotic behavior of dynamical systems in a broad sense, along with their applications in variational analysis and optimization.

Caracteristici

Self-contained, including all necessary functional and convex analysis background Blends theory and practice, focusing on algorithms, examples and applications Complete yet concise, both in depth and bibliography