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A vertex with a large degree, also called a heavy node, results in a large diagonal entry in the Laplacian matrix dominating the matrix properties. Normalization is aimed to make the influence of such vertices more equal to that of other vertices, by dividing the entries of the Laplacian matrix by the vertex degrees.
In the mathematical field of algebraic graph theory, the degree matrix of an undirected graph is a diagonal matrix which contains information about the degree of each vertex—that is, the number of edges attached to each vertex. [1]
Sometimes an extension of the domain of the edge weight function to is considered (with the resulting function still being called the edge weight function) by setting (,) = whenever (,). In applications each graph vertex x ∈ V {\displaystyle x\in V} usually represents a single entity in the given data, e.g., elements of a finite data set ...
In mathematics, the discrete Laplace operator is an analog of the continuous Laplace operator, defined so that it has meaning on a graph or a discrete grid.For the case of a finite-dimensional graph (having a finite number of edges and vertices), the discrete Laplace operator is more commonly called the Laplacian matrix.
A fan graph is a graph on n + 1 vertices where there is an edge between vertex i and n + 1 for all i = 1, 2, 3, …, n, and there is an edge between vertex i and i + 1 for all i = 1, 2, 3, …, n – 1. The resistance distance between vertex n + 1 and vertex i ∈ {1, 2, 3, …, n} is +
The discrete Laplacian (or Kirchhoff matrix) is obtained from the oriented incidence matrix B(G) by the formula (). The integral cycle space of a graph is equal to the null space of its oriented incidence matrix, viewed as a matrix over the integers or real or complex numbers.
By Kirchhoff's theorem, the number of spanning trees in a graph is counted by a cofactor of the Laplacian matrix. However, the Laplacian characteristic polynomial does not satisfy DC. By studying Laplacians with vertex weights, one can find a deletion-contraction relation between the scaled vertex-weighted Laplacian characteristic polynomials. [4]
Laplacian smoothing is an algorithm to smooth a polygonal mesh. [ 1 ] [ 2 ] For each vertex in a mesh, a new position is chosen based on local information (such as the position of neighbours) and the vertex is moved there.