On pebbling threshold functions for graph sequences

被引:11
|
作者
Czygrinow, A
Eaton, N
Hurlbert, G
Kayll, PM [1 ]
机构
[1] Arizona State Univ, Dept Math Sci, Tempe, AZ 85287 USA
[2] Arizona State Univ, Dept Math, Tempe, AZ 85287 USA
[3] Univ Rhode Isl, Dept Math, Kingston, RI 02881 USA
关键词
pebbling number; threshold function;
D O I
10.1016/S0012-365X(01)00163-7
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Given a connected graph G, and a distribution of t pebbles to the vertices of G, a pebbling step consists of removing two pebbles from a vertex v and placing one pebble on a neighbor of v. For a particular vertex r, the distribution is r-solvable if it is possible to place a pebble on r after a finite number of pebbling steps, The distribution is solvable if it is r-solvable for every r. The pebbling number of G is the least number t, so that every distribution of t pebbles is solvable. In this paper we are not concerned with such an absolute guarantee but rather an almost sure guarantee. A threshold function for a sequence of graphs G = (G(1), G(2),..., G(n),...), where G(n) has n vertices, is any function t(0)(n) such that almost all distributions of t pebbles are solvable when t much greater than t(0), and such that almost none are solvable when t much less than t(0). We give bounds on pebbling threshold functions for the sequences of cliques, stars, wheels, cubes, cycles and paths. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:93 / 105
页数:13
相关论文
共 42 条
  • [31] Relations between threshold and k-interval Boolean functions
    David Kronus
    Annals of Operations Research, 2011, 188 : 263 - 278
  • [32] Asymptotics of the number of threshold functions on a two-dimensional rectangular grid
    Haukkanen, Pentti
    Merikoski, Jorma K.
    DISCRETE APPLIED MATHEMATICS, 2013, 161 (1-2) : 13 - 18
  • [33] Asymptotics of the Number of Threshold Functions and the Singularity Probability of Random {±1}-Matrices
    A. A. Irmatov
    Doklady Mathematics, 2020, 101 : 247 - 249
  • [34] Generation of Reducts and Threshold Functions Using Discernibility and Indiscernibility Matrices for Classification
    Ishii, Naohiro
    Torii, Ippei
    Iwata, Kazunori
    Odagiri, Kazuya
    Nakashima, Toyoshiro
    ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, 2018, 650 : 159 - 170
  • [35] Asymptotics of the Number of Threshold Functions and the Singularity Probability of Random {±1}-Matrices
    Irmatov, A. A.
    DOKLADY MATHEMATICS, 2020, 101 (03) : 247 - 249
  • [36] A characterization of 2-threshold functions via pairs of prime segments
    Zamaraeva, Elena
    Zunic, Jovisa
    THEORETICAL COMPUTER SCIENCE, 2022, 919 : 1 - 17
  • [37] Circulant discrete dynamical systems with threshold functions of at most three variables
    Batueva T.C.-D.
    Journal of Applied and Industrial Mathematics, 2016, 10 (1) : 51 - 60
  • [38] Blind separation of signals with mixed kurtosis signs using threshold activation functions
    Mathis, H
    von Hoff, TP
    Joho, M
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 12 (03): : 618 - 624
  • [39] A Generalized Approach to Implement Efficient CMOS-Based Threshold Logic Functions
    Mozaffari, Seyed Nima
    Tragoudas, Spyros
    Haniotakis, Themistoklis
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2018, 65 (03) : 946 - 959
  • [40] Ultrasound signal processing based on joint GWO-VMD wavelet threshold functions
    Li, Hu
    Li, Songsong
    Sun, Jiao
    Huang, Benchi
    Zhang, Jiaqi
    Gao, Mingyang
    MEASUREMENT, 2024, 226