scholarly journals The generalized distance spectrum of a graph and applications

Author(s):  
Lee DeVille
Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 169 ◽  
Author(s):  
Abdollah Alhevaz ◽  
Maryam Baghipur ◽  
Hilal A. Ganie ◽  
Yilun Shang

Let G be a simple connected graph. In this paper, we study the spectral properties of the generalized distance matrix of graphs, the convex combination of the symmetric distance matrix D ( G ) and diagonal matrix of the vertex transmissions T r ( G ) . We determine the spectrum of the join of two graphs and of the join of a regular graph with another graph, which is the union of two different regular graphs. Moreover, thanks to the symmetry of the matrices involved, we study the generalized distance spectrum of the graphs obtained by generalization of the join graph operation through their eigenvalues of adjacency matrices and some auxiliary matrices.


Mathematics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 17 ◽  
Author(s):  
Abdollah Alhevaz ◽  
Maryam Baghipur ◽  
Hilal A. Ganie ◽  
Yilun Shang

The generalized distance matrix D α ( G ) of a connected graph G is defined as D α ( G ) = α T r ( G ) + ( 1 − α ) D ( G ) , where 0 ≤ α ≤ 1 , D ( G ) is the distance matrix and T r ( G ) is the diagonal matrix of the node transmissions. In this paper, we extend the concept of energy to the generalized distance matrix and define the generalized distance energy E D α ( G ) . Some new upper and lower bounds for the generalized distance energy E D α ( G ) of G are established based on parameters including the Wiener index W ( G ) and the transmission degrees. Extremal graphs attaining these bounds are identified. It is found that the complete graph has the minimum generalized distance energy among all connected graphs, while the minimum is attained by the star graph among trees of order n.


Author(s):  
Anna G. Matveeva ◽  
Victoria N. Syryamina ◽  
Vyacheslav M. Nekrasov ◽  
Michael K. Bowman

Non-uniform schemes for collection of pulse dipole spectroscopy data can decrease and redistribute noise in the distance spectrum for increased sensitivity and throughput.


1973 ◽  
Vol 21 (2) ◽  
pp. 121-132 ◽  
Author(s):  
Michael Festing

SUMMARYThe shape of the mandible in. nine sublines of C57BL/Gr, seven other strains of ‘C57 ancestry’ and four unrelated strains was studied by multivariate techniques. The generalized distance function was used to classify individuals in the groups which they most closely resembled. The degree of misclassification depended on the pedigree relationship between strains and sublines. The generalized distance between pairs of subline centeroids was also highly correlated (r = 0·60) with the number of generations between them. A canonical variate analysis was used to reduce the dimensionality so that a graphical display of the relationships between strains and sublines could be made. The results agreed closely with the classification analysis. It was concluded that the shape of the mandible could be used for subline identification though the accuracy of this technique depends on how closely the sublines are related.


1972 ◽  
Vol 4 (3) ◽  
pp. 263-273
Author(s):  
David M. Jackson ◽  
Lee J. White

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