Results 31 to 40 of about 121,408 (279)
Incidence matrices and line graphs of mixed graphs
Special Matrices, 2023 In the theory of line graphs of undirected graphs, there exists an important theorem linking the incidence matrix of the root graph to the adjacency matrix of its line graph. For directed or mixed graphs, however, there exists no analogous result.
Abudayah Mohammad +2 more
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Applied Sciences, 2022 Adjacency matrix visualization is a common method for presenting graph data, and the Focus+Context technique can be used to explore the details of the ROI (region of interest).
Tiemeng Li +3 more
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Factorization threshold models for scale-free networks generation [PDF]
, 2016 Many real networks such as the World Wide Web, financial, biological, citation and social networks have a power-law degree distribution. Networks with this feature are also called scale-free.
Artikov, Akmal +3 more
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Graph Spectral Properties of Deterministic Finite Automata
, 2014 We prove that a minimal automaton has a minimal adjacency matrix rank and a minimal adjacency matrix nullity using equitable partition (from graph spectra theory) and Nerode partition (from automata theory). This result naturally introduces the notion of
A. Goldberg +5 more
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On the Adjacency, Laplacian, and Signless Laplacian Spectrum of Coalescence of Complete Graphs
Journal of Mathematics, 2016 Coalescence as one of the operations on a pair of graphs is significant due to its simple form of chromatic polynomial. The adjacency matrix, Laplacian matrix, and signless Laplacian matrix are common matrices usually considered for discussion under ...
S. R. Jog, Raju Kotambari
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Vertex adjacencies in the set covering polyhedron [PDF]
, 2017 We describe the adjacency of vertices of the (unbounded version of the) set covering polyhedron, in a similar way to the description given by Chvatal for the stable set polytope.
Aguilera, Néstor E. +2 more
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Deep Learning Techniques for Community Detection in Social Networks
IEEE Access, 2020 Graph embedding is an effective yet efficient way to convert graph data into a low dimensional space. In recent years, deep learning has applied on graph embedding and shown outstanding performance.
Ling Wu +4 more
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On α-adjacency energy of graphs and Zagreb index
AKCE International Journal of Graphs and Combinatorics, 2021 Let A(G) be the adjacency matrix and D(G) be the diagonal matrix of the vertex degrees of a simple connected graph G. Nikiforov defined the matrix of the convex combinations of D(G) and A(G) as for If are the eigenvalues of (which we call α-adjacency ...
S. Pirzada +3 more
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Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
KAMG: A Tool for Converting Blood Ties and Affinity Ties into Adjacency Matrices
Journal of Open Research Software, 2016 Kinship Adjacency Matrix Generator (KAMG) is a browser-based software for creating adjacency matrices using the information of kinship ties. Specifically, it is capable of converting the family trees in the format of GEDCOM files into adjacency matrices ...
Hang Xiong, Pin Xiong, Hui Xiong
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