Fenchel-Moreau and Primal/Dual Optimization Problems: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| Line 2: | Line 2: | ||
==Background on Conjugate Functions== | ==Background on Conjugate Functions== | ||
Let''X'' be a normed vector space, and let ''X*'' denote its topological dual. Given an extended real-valued function <math> | Let''X'' be a normed vector space, and let ''X*'' denote its topological dual. Given an extended real-valued function <math> f: X \to \mathbb{R} \cup \{+\infty\} </math>, its ''convex conjugate'' <math>f^*:X^* \to \mathbb{R} \cup \{+\infty\}</math> is defined by | ||
:<math> test </math> | :<math> test </math> | ||
Revision as of 22:24, 7 April 2020
The Fenchel-Moreau Theorem is a fundamental result in convex analysis, characterizing the class of functions for which a function equals its biconjugate. A key consequence of this theorem is the equivalence of primal and dual optimization problems.
Background on Conjugate Functions
LetX be a normed vector space, and let X* denote its topological dual. Given an extended real-valued function , its convex conjugate is defined by
[1]
References
- ↑ H. Brezis, Functional Analysis.