Results 41 to 50 of about 2,218,762 (336)
Computing the Permanent of the Laplacian Matrices of Nonbipartite Graphs
Journal of Mathematics, 2021 Let G be a graph with Laplacian matrix LG. Denote by per LG the permanent of LG. In this study, we investigate the problem of computing the permanent of the Laplacian matrix of nonbipartite graphs.
Xiaoxue Hu, Grace Kalaso
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On graphs with distance Laplacian eigenvalues of multiplicity n−4
AKCE International Journal of Graphs and Combinatorics, 2023 Let G be a connected simple graph with n vertices. The distance Laplacian matrix [Formula: see text] is defined as [Formula: see text], where [Formula: see text] is the diagonal matrix of vertex transmissions and [Formula: see text] is the distance ...
Saleem Khan, S. Pirzada, A. Somasundaram
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Monophonic Distance Laplacian Energy of Transformation Graphs Sn^++-,Sn^{+-+},Sn^{+++}
Ratio Mathematica, 2023 Let $G$ be a simple connected graph of order $n$, $v_{i}$ its vertex. Let $\delta^{L}_{1}, \delta^{L}_{2}, \ldots, \delta^{L}_{n}$ be the eigenvalues of the distance Laplacian matrix $D^{L}$ of $G$. The distance Laplacian energy is denoted by $LE_{D}(G)$.
Diana R, Binu Selin T
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Chromatic number and signless Laplacian spectral radius of graphs [PDF]
Transactions on Combinatorics, 2022 For any simple graph $G$, the signless Laplacian matrix of $G$ is defined as $D(G)+A(G)$, where $D(G)$ and $A(G)$ are the diagonal matrix of vertex degrees and the adjacency matrix of $G$, respectively.
Mohammad Reza Oboudi
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Sparse Graph Learning Under Laplacian-Related Constraints
IEEE Access, 2021 We consider the problem of learning a sparse undirected graph underlying a given set of multivariate data. We focus on graph Laplacian-related constraints on the sparse precision matrix that encodes conditional dependence between the random variables ...
Jitendra K. Tugnait
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On the spectra of nonsymmetric Laplacian matrices [PDF]
, 2005 A Laplacian matrix is a square real matrix with nonpositive off-diagonal entries and zero row sums. As a matrix associated with a weighted directed graph, it generalizes the Laplacian matrix of an ordinary graph.
Anderson +19 more
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The normalized distance Laplacian
Special Matrices, 2021 The distance matrix 𝒟(G) of a connected graph G is the matrix containing the pairwise distances between vertices. The transmission of a vertex vi in G is the sum of the distances from vi to all other vertices and T(G) is the diagonal matrix of ...
Reinhart Carolyn
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Incremental eigenpair computation for graph Laplacian matrices: theory and applications [PDF]
, 2017 The smallest eigenvalues and the associated eigenvectors (i.e., eigenpairs) of a graph Laplacian matrix have been widely used for spectral clustering and community detection. However, in real-life applications, the number of clusters or communities (say,
Al Hasan, Mohammad +2 more
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More on Spectral Analysis of Signed Networks
Complexity, 2018 Spectral graph theory plays a key role in analyzing the structure of social (signed) networks. In this paper we continue to study some properties of (normalized) Laplacian matrix of signed networks. Sufficient and necessary conditions for the singularity
Guihai Yu, Hui Qu
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On graphs with a few distinct reciprocal distance Laplacian eigenvalues
AIMS Mathematics, 2023 For a $ \nu $-vertex connected graph $ \Gamma $, we consider the reciprocal distance Laplacian matrix defined as $ RD^L(\Gamma) = RT(\Gamma)-RD(\Gamma) $, i.e., $ RD^L(\Gamma) $ is the difference between the diagonal matrix of the reciprocal distance ...
Milica Anđelić +2 more
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