logo
    The entire mean weighted first-passage time on infinite families of weighted tree networks
    23
    Citation
    31
    Reference
    10
    Related Paper
    Citation Trend
    Abstract:
    We propose the entire mean weighted first-passage time (EMWFPT) for the first time in the literature. The EMWFPT is obtained by the sum of the reciprocals of all nonzero Laplacian eigenvalues on weighted networks. Simplified calculation of EMWFPT is the key quantity in the study of infinite families of weighted tree networks, since the weighted complex systems have become a fundamental mechanism for diverse dynamic processes. We base on the relationships between characteristic polynomials at different generations of their Laplacian matrix and Laplacian eigenvalues to compute EMWFPT. This technique of simplified calculation of EMWFPT is significant both in theory and practice. In this paper, firstly, we introduce infinite families of weighted tree networks with recursive properties. Then, we use the sum of the reciprocals of all nonzero Laplacian eigenvalues to calculate EMWFPT, which is equal to the average of MWFPTs over all pairs of nodes on infinite families of weighted networks. In order to compute EMWFPT, we try to obtain the analytical expressions for the sum of the reciprocals of all nonzero Laplacian eigenvalues. The key step here is to calculate the constant terms and the coefficients of first-order terms of characteristic polynomials. Finally, we obtain analytically the closed-form solutions to EMWFPT on the weighted tree networks and show that the leading term of EMWFPT grows superlinearly with the network size.
    Keywords:
    Tree (set theory)
    Characteristic polynomial
    Matrix (chemical analysis)
    Base (topology)
    A Laplacian spectral method combined with shape context analysis was proposed for point pattern matching. This work mainly focused on the problem of how to render the Laplacian spectral method robust for random position jitter. Firstly, the initial correspondence probabilities were computed by using the eigenvectors and eigenvalues of the Laplacian matrix as well as the method of doubly stochastic matrix. Secondly, local similarity evaluated by shape context was embedded into the Laplacian spectral method to refine the results of spectral correspondence via a probabilistic relaxation approach. Experiments on both real-world and synthetic data demonstrate that the method possesses comparatively high accuracy.
    Similarity (geometry)
    Matrix (chemical analysis)
    Citations (1)
    The Detour distance laplacian energy of a simple connected graph \(G\) is defined as the sum of the absolute values of the Eigen values of the detour distance laplacian matrix of \(G\). In this paper, the bounds for detour distance laplacian energy is obtain and also the detour distance laplacian energy of standard graphs and the Cartesian product of certain graphs with \(P_2\) are computed.
    Cartesian product
    Distance matrix
    Resistance Distance
    Vector Laplacian
    Citations (4)
    Spectral Radius
    Algebraic connectivity
    Spectral graph theory
    Spectral Clustering
    Resistance Distance
    Spectral Properties
    Citations (7)
    Introduction/purpose: The Laplacian energy (LE) is the sum of absolute values of the terms μi-2m/n, where μi, i=1,2,…,n, are the eigenvalues of the Laplacian matrix of the graph G with n vertices and m edges. The basic results of the theory of LE are outlined, and some new obtained. Methods: Spectral theory of Laplacian matrices is applied. Results: A new class of lower bounds for LE is derived. Conclusion: The paper contributes to the Laplacian spectral theory and tp the theory of graph energies.
    Spectral graph theory
    Spectral Theory
    Resistance Distance
    Spectral Properties
    Matrix (chemical analysis)
    Citations (1)
    In this paper, we examine the properties of the Laplacian matrix defined on signed networks, referred to as the signed Laplacian matrix, from a graph-theoretic perspective. The connection between the stability of the signed Laplacian with the cut set of the network is established. This is then followed by relating and the number of negative eigenvalues of the signed Laplacian to the number of negatively weighted edges in the network. In order to stabilize the signed Laplacian dynamics, a distributed diagonal compensation approach is proposed; we show that this compensation is closely related to the structural balance of the network. Furthermore, the influence of the external input exerted on the signed Laplacian dynamics is investigated.
    Signed graph
    Diagonal matrix
    Network Dynamics
    Resistance Distance
    Citations (23)
    In this paper, we give some lower bounds for several eigenvalues. Firstly, we investigate the eigenvalues $\lambda_i$ of the Laplace operator and prove a sharp lower bound. Moreover, we extent this estimate of the eigenvalues to general cases. Secondly, we study the eigenvalues $\Gamma_i$ for the clamped plate problem and deliver a sharp bound for the clamped plate problem for arbitrary dimension.
    Operator (biology)
    Citations (0)
    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 of Laplacian matrix are given. We determine the correspondence between the balance of signed network and the singularity of its Laplacian matrix. An expression of the determinant of Laplacian matrix is present. The symmetry about 1 of eigenvalues of normalized Laplacian matrix is discussed. We determine that the integer 2 is an eigenvalue of normalized Laplacian matrix if and only if the signed network is balanced and bipartite. Finally an expression of the coefficient of normalized Laplacian characteristic polynomial is present.
    Matrix (chemical analysis)
    Spectral graph theory
    Citations (1)