Undergraduate Convexity
Problems and Solutions
Nonfiction, Science & Nature, Mathematics, Vector Analysis, Geometry
| Author: | Mikkel Slot Nielsen, Victor Ulrich Rohde | ISBN: | 9789813143661 |
| Publisher: | World Scientific Publishing Company | Publication: | September 8, 2016 |
| Imprint: | WSPC | Language: | English |
| Author: | Mikkel Slot Nielsen, Victor Ulrich Rohde |
| ISBN: | 9789813143661 |
| Publisher: | World Scientific Publishing Company |
| Publication: | September 8, 2016 |
| Imprint: | WSPC |
| Language: | English |
This solutions manual thoroughly goes through the exercises found in Undergraduate Convexity: From Fourier and Motzkin to Kuhn and Tucker. Several solutions are accompanied by detailed illustrations and intuitive explanations. This book will pave the way for students to easily grasp the multitude of solution methods and aspects of convex sets and convex functions.
Contents:
- Fourier–Motzkin Elimination
- Affine Subspaces
- Convex Subsets
- Polyhedra
- Computations with Polyhedra
- Closed Convex Subsets and Separating Hyperplanes
- Convex Functions
- Differentiable Functions of Several Variables
- Convex Functions of Several Variables
- Convex Optimization
- Appendices: Analysis; Linear (In)dependence and the Rank of a Matrix
Readership: Undergraduates focusing on convexity and optimization.
Key Features:
- Extensive solutions to all exercises in Undergraduate Convexity
- Many illustrations
- Complements Undergraduate Convexity with insights useful for solving the exercises
This solutions manual thoroughly goes through the exercises found in Undergraduate Convexity: From Fourier and Motzkin to Kuhn and Tucker. Several solutions are accompanied by detailed illustrations and intuitive explanations. This book will pave the way for students to easily grasp the multitude of solution methods and aspects of convex sets and convex functions.
Contents:
- Fourier–Motzkin Elimination
- Affine Subspaces
- Convex Subsets
- Polyhedra
- Computations with Polyhedra
- Closed Convex Subsets and Separating Hyperplanes
- Convex Functions
- Differentiable Functions of Several Variables
- Convex Functions of Several Variables
- Convex Optimization
- Appendices: Analysis; Linear (In)dependence and the Rank of a Matrix
Readership: Undergraduates focusing on convexity and optimization.
Key Features:
- Extensive solutions to all exercises in Undergraduate Convexity
- Many illustrations
- Complements Undergraduate Convexity with insights useful for solving the exercises
