The Minimum Number of Interior H-Points of Convex H-Dodecagons

被引:0
|
作者
Wei, X. [1 ]
Wang, W. [1 ]
Guo, Z. [1 ]
机构
[1] Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R China
基金
中国国家自然科学基金;
关键词
discrete geometry; lattice polygon; H-polygon; interior hull; outer hull; LATTICE POLYGONS;
D O I
10.1134/S0001434620030141
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
An H-polygon is a simple polygon whose vertices are H-points, which are points of the set of vertices of a tiling of Double-struck capital R-2 by regular hexagons of unit edge. Let G(v) denote the least possible number of H-points in the interior of a convex H-polygon K with v vertices. In this paper we prove that G(12) = 12.
引用
收藏
页码:509 / 517
页数:9
相关论文
共 26 条
  • [21] n-Points Inequalities of Hermite-Hadamard Type for h-Convex Functions on Linear Spaces
    Dragomir, S. S.
    ARMENIAN JOURNAL OF MATHEMATICS, 2016, 8 (01): : 38 - 57
  • [22] A correlation between the mean polarizability of the "kinked" polycyclic aromatic hydrocarbons and the number of H...H bond critical points predicted by Atoms-in-Molecules theory
    Sabirov, D. Sh.
    COMPUTATIONAL AND THEORETICAL CHEMISTRY, 2014, 1030 : 81 - 86
  • [23] Analysis of the Regularization Parameters of Primal–Dual Interior Method for Convex Objectives Applied to 1H Low Field Nuclear Magnetic Resonance Data Processing
    Salvatore Campisi-Pinto
    Ofer Levi
    Diamanta Benson
    Meir Cohen
    Maysa Teixeira Resende
    Michael Saunders
    Charles Linder
    Zeev Wiesman
    Applied Magnetic Resonance, 2018, 49 : 1129 - 1150
  • [24] Analysis of the Regularization Parameters of Primal-Dual Interior Method for Convex Objectives Applied to 1H Low Field Nuclear Magnetic Resonance Data Processing
    Campisi-Pinto, Salvatore
    Levi, Ofer
    Benson, Diamanta
    Cohen, Meir
    Resende, Maysa Teixeira
    Saunders, Michael
    Linder, Charles
    Wiesman, Zeev
    APPLIED MAGNETIC RESONANCE, 2018, 49 (10) : 1129 - 1150
  • [25] Correction to: Analysis of the Regularization Parameters of Primal–Dual Interior Method for Convex Objectives Applied to 1H Low Field Nuclear Magnetic Resonance Data Processing
    Salvatore Campisi-Pinto
    Ofer Levi
    Diamanta Benson
    Meir Cohen
    Maysa Teixeira Resende
    Michael Saunders
    Charles Linder
    Zeev Wiesman
    Applied Magnetic Resonance, 2019, 50 : 521 - 521
  • [26] Analysis of the Regularization Parameters of Primal-Dual Interior Method for Convex Objectives Applied to 1H Low Field Nuclear Magnetic Resonance Data Processing (vol 49, pg 1129, 2018)
    Campisi-Pinto, Salvatore
    Levi, Ofer
    Benson, Diamanta
    Cohen, Meir
    Resende, Maysa Teixeira
    Saunders, Michael
    Linder, Charles
    Wiesman, Zeev
    APPLIED MAGNETIC RESONANCE, 2019, 50 (1-3) : 521 - 521