scholarly journals Identifying network structure similarity using spectral graph theory

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Ralucca Gera ◽  
L. Alonso ◽  
Brian Crawford ◽  
Jeffrey House ◽  
J. A. Mendez-Bermudez ◽  
...  
Keyword(s):  
Graph Theory ◽  
Network Structure ◽  
Spectral Graph Theory ◽  
Spectral Graph ◽  
Structure Similarity

Graph Structure Similarity using Spectral Graph Theory

2016 ◽  
pp. 209-221 ◽  
Author(s):  
Brian Crawford ◽  
Ralucca Gera ◽  
Jeffrey House ◽  
Thomas Knuth ◽  
Ryan Miller
Keyword(s):  
Graph Theory ◽  
Spectral Graph Theory ◽  
Graph Structure ◽  
Spectral Graph ◽  
Structure Similarity

On Two Conjectures of Spectral Graph Theory

2018 ◽  
Vol 44 (1) ◽  
pp. 43-51
Author(s):  
Kinkar Ch. Das ◽  
Muhuo Liu
Keyword(s):  
Graph Theory ◽  
Spectral Graph Theory ◽  
Spectral Graph

scholarly journals Nordhaus–Gaddum-Type Relations for Arithmetic-Geometric Spectral Radius and Energy

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yajing Wang ◽  
Yubin Gao
Keyword(s):  
Graph Theory ◽  
Spectral Radius ◽  
Adjacency Matrix ◽  
Upper Bounds ◽  
Simple Graph ◽  
Spectral Graph Theory ◽  
Extremal Graphs ◽  
Spectral Graph ◽  
Vertex Set

Spectral graph theory plays an important role in engineering. Let G be a simple graph of order n with vertex set V=v1,v2,…,vn. For vi∈V, the degree of the vertex vi, denoted by di, is the number of the vertices adjacent to vi. The arithmetic-geometric adjacency matrix AagG of G is defined as the n×n matrix whose i,j entry is equal to di+dj/2didj if the vertices vi and vj are adjacent and 0 otherwise. The arithmetic-geometric spectral radius and arithmetic-geometric energy of G are the spectral radius and energy of its arithmetic-geometric adjacency matrix, respectively. In this paper, some new upper bounds on arithmetic-geometric energy are obtained. In addition, we present the Nordhaus–Gaddum-type relations for arithmetic-geometric spectral radius and arithmetic-geometric energy and characterize corresponding extremal graphs.

An Algorithm for Determining the Position and Orientation of 3-D Objects from Images Using Spectral Graph Theory

2015 ◽  
Vol 770 ◽  
pp. 585-591
Author(s):  
Alexey Barinov ◽  
Aleksey Zakharov
Keyword(s):  
Graph Theory ◽  
Adjacency Matrix ◽  
Spectral Decomposition ◽  
Spectral Graph Theory ◽  
Feature Points ◽  
Image Comparison ◽  
Spectral Graph ◽  
Position And Orientation ◽  
Weighted Adjacency Matrix

This paper describes an algorithm for computing the position and orientation of 3-D objects by comparing graphs. The graphs are based on feature points of the image. Comparison is performed by a spectral decomposition with obtaining eigenvectors of weighted adjacency matrix of the graph.

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