On convolution of L-convex functions

Research output: Contribution to journalArticle

Abstract

L2-convex functions, which are the convolution of two L-convex functions, constitute a wide class of discrete convex functions in discrete convex analysis, a unified framework of discrete optimization, proposed by Murota. This article shows a technical result that any L2-convex function can be represented by the convolution of two L-convex functions attaining the infimum in the definition of the convolution. This result gives simple proofs for several known results on L2-convex functions.

Original languageEnglish
Pages (from-to)231-245
Number of pages15
JournalOptimization Methods and Software
Volume18
Issue number2
DOIs
Publication statusPublished - 2003 Apr
Externally publishedYes

Fingerprint

Convolution
Convex function
Convex Analysis
Discrete Optimization

Keywords

  • Convolution
  • Discrete convex analysis
  • L-/L-convex functions

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software
  • Applied Mathematics
  • Control and Optimization
  • Management Science and Operations Research

Cite this

On convolution of L-convex functions. / Tamura, Akihisa.

In: Optimization Methods and Software, Vol. 18, No. 2, 04.2003, p. 231-245.

Research output: Contribution to journalArticle

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