Optimierung und Approximation: Ausgabe 2

Walter de Gruyter
Free sample

Die zweite, überarbeitete und erweiterte Auflage dieses Lehrbuchs liefert eine fundierte mathematische Einführung in die Thematik. Besonderer Wert wird auf möglichst einfache Beweise gelegt, die zugleich eine geometrische Anschauung erlauben. Zahlreiche Übungsaufgaben und Beispiele ergänzen den Inhalt.
  • Überarbeitete Neuauflage eines bekannten Lehrbuchs
  • Fundierte mathematische Einführung in die Thematik
  • Mit einfachen und anschaulichen Beweisen
Read more

About the author

Peter Kosmol , Christian-Albrechts-Universität, Kiel

Read more

Additional Information

Walter de Gruyter
Read more
Published on
Mar 26, 2010
Read more
Read more
Read more
Read more
Best For
Read more
Read more
Mathematics / Calculus
Mathematics / Functional Analysis
Mathematics / General
Mathematics / Linear & Nonlinear Programming
Mathematics / Mathematical Analysis
Read more
Content Protection
This content is DRM protected.
Read more

Reading information

Smartphones and Tablets

Install the Google Play Books app for Android and iPad/iPhone. It syncs automatically with your account and allows you to read online or offline wherever you are.

Laptops and Computers

You can read books purchased on Google Play using your computer's web browser.

eReaders and other devices

To read on e-ink devices like the Sony eReader or Barnes & Noble Nook, you'll need to download a file and transfer it to your device. Please follow the detailed Help center instructions to transfer the files to supported eReaders.
This is an essentially self-contained book on the theory of convex functions and convex optimization in Banach spaces, with a special interest in Orlicz spaces.

Approximate algorithms based on the stability principles and the solution of the corresponding nonlinear equations are developed in this text. A synopsis of the geometry of Banach spaces, aspects of stability and the duality of different levels of differentiability and convexity is developed. A particular emphasis is placed on the geometrical aspects of strong solvability of a convex optimization problem: it turns out that this property is equivalent to local uniform convexity of the corresponding convex function. This treatise also provides a novel approach to the fundamental theorems of Variational Calculus based on the principle of pointwise minimization of the Lagrangian on the one hand and convexification by quadratic supplements using the classical Legendre-Ricatti equation on the other.

The reader should be familiar with the concepts of mathematical analysis and linear algebra. Some awareness of the principles of measure theory will turn out to be helpful. The book is suitable for students of the second half of undergraduate studies, and it provides a rich set of material for a master course on linear and nonlinear functional analysis. Additionally it offers novel aspects at the advanced level.

From the contents:

Approximation and Polya Algorithms in Orlicz Spaces Convex Sets and Convex Functions Numerical Treatment of Non-linear Equations and Optimization Problems Stability and Two-stage Optimization Problems Orlicz Spaces, Orlicz Norm and Duality Differentiability and Convexity in Orlicz Spaces Variational Calculus
©2018 GoogleSite Terms of ServicePrivacyDevelopersArtistsAbout Google|Location: United StatesLanguage: English (United States)
By purchasing this item, you are transacting with Google Payments and agreeing to the Google Payments Terms of Service and Privacy Notice.