Results 51 to 60 of about 120,979 (218)
MathematicsFor network graphs, numerous graph features are intimately linked to eigenvalues of the Laplacian matrix, such as connectivity and diameter. Thus, it is very important to solve eigenvalues of the Laplacian matrix for graphs.
Changlei Zhan, Xiangyu Li, Jie Chen
doaj +1 more source
Signless Laplacian determinations of some graphs with independent edges
Karpatsʹkì Matematičnì Publìkacìï, 2018 Let $G$ be a simple undirected graph. Then the signless Laplacian matrix of $G$ is defined as $D_G + A_G$ in which $D_G$ and $A_G$ denote the degree matrix and the adjacency matrix of $G$, respectively.
R. Sharafdini, A.Z. Abdian
doaj +1 more source
A study on determination of some graphs by Laplacian and signless Laplacian permanental polynomials
AKCE International Journal of Graphs and Combinatorics, 2023 The permanent of an n × n matrix [Formula: see text] is defined as [Formula: see text] where the sum is taken over all permutations σ of [Formula: see text] The permanental polynomial of M, denoted by [Formula: see text] is [Formula: see text] where In ...
Aqib Khan +2 more
doaj +1 more source
Laplacian integral signed graphs with few cycles
AIMS Mathematics, 2023 A connected graph with n vertices and m edges is called k-cyclic graph if k=m−n+1. We call a signed graph is Laplacian integral if all eigenvalues of its Laplacian matrix are integers.
Dijian Wang, Dongdong Gao
doaj +1 more source
Communications in Advanced Mathematical Sciences, 2018 The signless Laplacian eigenvalues of a graph $G$ are eigenvalues of the matrix $Q(G) = D(G) + A(G)$, where $D(G)$ is the diagonal matrix of the degrees of the vertices in $G$ and $A(G)$ is the adjacency matrix of $G$.
Rao Li
doaj +1 more source
Laplacian Matrix for Dimensionality Reduction and Clustering [PDF]
, 2020 Many problems in machine learning can be expressed by means of a graph with nodes representing training samples and edges representing the relationship between samples in terms of similarity, temporal proximity, or label information. Graphs can in turn be represented by matrices. A special example is the Laplacian matrix, which allows us to assign each
Laurenz Wiskott, Fabian Schönfeld
openaire +2 more sources
Eigenvector-based identification of bipartite subgraphs
, 2018 We report our experiments in identifying large bipartite subgraphs of simple connected graphs which are based on the sign pattern of eigenvectors belonging to the extremal eigenvalues of different graph matrices: adjacency, signless Laplacian, Laplacian,
Asratian +42 more
core +1 more source
Primer for the algebraic geometry of sandpiles [PDF]
, 2011 The Abelian Sandpile Model (ASM) is a game played on a graph realizing the dynamics implicit in the discrete Laplacian matrix of the graph. The purpose of this primer is to apply the theory of lattice ideals from algebraic geometry to the Laplacian ...
Perkinson, David +2 more
core
The p-spectral radius of the Laplacian matrix
Applicable Analysis and Discrete Mathematics, 2018 The p-spectral radius of a graph G=(V,E) with adjacency matrix A is defined as ?(p)(G) = max||x||p=1 xT Ax. This parameter shows connections with graph invariants, and has been used to generalize some extremal problems. In this work, we define the p-spectral radius of the Laplacian matrix L as ?(p)(G) = max||x||p=1 xT Lx.
Borba, Elizandro Max +3 more
openaire +2 more sources
A Note on the Laplacian Energy of the Power Graph of a Finite Cyclic Group
Sakarya Üniversitesi Fen Bilimleri Enstitüsü DergisiIn this study, the Laplacian matrix concept for the power graph of a finite cyclic group is redefined by considering the block matrix structure. Then, with the help of the eigenvalues of the Laplacian matrix in question, the concept of Laplacian energy ...
Şerife Büyükköse +1 more
doaj +1 more source