Results 11 to 20 of about 601,789 (263)
Entropy measures of distance matrix [PDF]
Discrete Mathematics Letters, 2022 Bonchev and Trinajstic defined two distance based entropy measures to measure the molecular branching of molecular graphs in 1977 [Information theory, distance matrix, and molecular branching, J. Chem. Phys., 38 (1977), 4517–4533]. In this paper we use these entropy measures which are based on distance matrices of graphs.
Bünyamin Şahin, Abdulgani Şahin
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A Distance-Preserving Matrix Sketch
Journal of Computational and Graphical Statistics, 2022 38 pages, 13 ...
Leland Wilkinson, Hengrui Luo
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On the rank of the distance matrix of graphs
Applied Mathematics and Computation, 2022 17 pages, 2 ...
Ezequiel Dratman +3 more
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Product distance matrix of a graph and squared distance matrix of a tree [PDF]
Applicable Analysis and Discrete Mathematics, 2013 Let G be a strongly connected, weighted directed graph. We define a product distance ?(i,j) for pairs i,j of vertices and form the corresponding product distance matrix. We obtain a formula for the determinant and the inverse of the product distance matrix.
BAPAT, RB, SIVASUBRAMANIAN, S
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On the distance matrix of a tree
Discrete Mathematics, 1976 AbstractFor a tree T on n vertices, let D(T)=(dij) denote the distance matrix of T, i.e., dij(T) is just the length of the unique path then the ith vertex and the jth vertex of T. Denote by ΔT(x) the characteristic polynom, of D(T), so that ΔT(x) = det(D(T) xl). In this paper, we investigate a number of properties of ΔT(x).
M. Edelberg +2 more
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Multi-distance support matrix machines [PDF]
Pattern Recognition Letters, 2019 Real-world data such as digital images, MRI scans and electroencephalography signals are naturally represented as matrices with structural information. Most existing classifiers aim to capture these structures by regularizing the regression matrix to be low-rank or sparse.
Yunfei Ye, Dong Han
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On Matrix Nearness Problems: Distance to Delocalization [PDF]
SIAM Journal on Matrix Analysis and Applications, 2015 This paper introduces two new matrix nearness problems that are intended to generalize the distance to instability and the distance to stability. They are named the distance to delocalization and the distance to localization due to their applicability in analyzing the robustness of eigenvalues with respect to arbitrary localization sets (domains) in ...
Vladimir R. Kostic +2 more
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Distance (signless) Laplacian spectrum of dumbbell graphs [PDF]
Transactions on Combinatorics, 2023 In this paper, we determine the distance Laplacian and distance signless Laplacian spectrum of generalized wheel graphs and a new class of graphs called dumbbell graphs.
Sakthidevi Kaliyaperumal +1 more
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Bounds for the Distance to the Nearest Correlation Matrix [PDF]
SIAM Journal on Matrix Analysis and Applications, 2016 Summary: In a wide range of practical problems correlation matrices are formed in such a way that, while symmetry and a unit diagonal are ensured, they may lack semidefiniteness. We derive a variety of new upper bounds for the distance from an arbitrary symmetric matrix to the nearest correlation matrix.
Nicholas J. Higham, Natasa Strabic
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On the distance eigenvalues of Cayley graphs
پژوهشهای ریاضی, 2022 In this paper, graphs are undirected and loop-free and groups are finite. By Cn, Kn and Km,n we mean the cycle graph with n vertices, the complete graph with n vertices and the complete bipartite graph with parts size m and n, respectively.
Majid Arezoomand
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