Results 21 to 30 of about 18,314 (299)

An integrated exploration of heat kernel invariant feature and manifolding technique for 3D object recognition system

open access: yesActa Scientiarum: Technology, 2023
Spectral Graph theory has been utilized frequently in the field of Computer Vision and Pattern Recognition to address challenges in the field of Image Segmentation and Image Classification.
Subramaniam Usha   +3 more
doaj   +1 more source

Computing the Permanent of the Laplacian Matrices of Nonbipartite Graphs

open access: yesJournal 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
doaj   +1 more source

Chromatic number and signless Laplacian spectral radius of graphs [PDF]

open access: yesTransactions 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
doaj   +1 more source

On graphs with distance Laplacian eigenvalues of multiplicity n−4

open access: yesAKCE 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
doaj   +1 more source

Monophonic Distance Laplacian Energy of Transformation Graphs Sn^++-,Sn^{+-+},Sn^{+++}

open access: yesRatio 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
doaj   +1 more source

An analog of Matrix Tree Theorem for signless Laplacians [PDF]

open access: yesLinear Algebra and its Applications, 2019
A spanning tree of a graph is a connected subgraph on all vertices with the minimum number of edges. The number of spanning trees in a graph $G$ is given by Matrix Tree Theorem in terms of principal minors of Laplacian matrix of $G$. We show a similar combinatorial interpretation for principal minors of signless Laplacian $Q$.
Keivan Hassani Monfared, Sudipta Mallik
openaire   +3 more sources

Spectral properties for the Laplacian of a generalized Wigner matrix [PDF]

open access: yesRandom Matrices: Theory and Applications, 2021
In this paper, we consider the spectrum of a Laplacian matrix, also known as Markov matrices where the entries of the matrix are independent but have a variance profile. Motivated by recent works on generalized Wigner matrices we assume that the variance profile gives rise to a sequence of graphons.
Chatterjee, A., Hazra, R.S.
openaire   +4 more sources

On the signless Laplacian and normalized signless Laplacian spreads of graphs [PDF]

open access: yes, 2023
summary:Let $G=(V,E)$, $V=\{v_1,v_2,\ldots ,v_n\}$, be a simple connected graph with $n$ vertices, $m$ edges and a sequence of vertex degrees $d_1\geq d_2\geq \cdots \geq d_n$.
Milovanović, Emina   +3 more
core   +1 more source

The normalized distance Laplacian

open access: yesSpecial 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
doaj   +1 more source

Sparse Graph Learning Under Laplacian-Related Constraints

open access: yesIEEE 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
doaj   +1 more source

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