Results 41 to 50 of about 2,643,042 (116)
Non-backtracking eigenvalues and eigenvectors of random regular graphs and hypergraphs [PDF]
arXiv, 2023 The non-backtracking operator of a graph is a powerful tool in spectral graph theory and random matrix theory. Most existing results for the non-backtracking operator of a random graph concern only eigenvalues or top eigenvectors. In this paper, we take the first step in analyzing its bulk eigenvector behaviors.
arxiv
Molecular van der Waals Space and Topological Indices from the Distance Matrix
Molecules, 2004 A comparative study of 36 molecular descriptors derived from the topologicaldistance matrix and van der Waals space is carried out within this paper.
Seiman Corina +6 more
doaj +1 more source
RECOGNITION OF HUMAN POSE FROM IMAGES BASED ON GRAPH SPECTRA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Recognition of human pose is an actual problem in computer vision. To increase the reliability of the recognition it is proposed to use structured information in the form of graphs.
A. A. Zakharov +2 more
doaj +1 more source
Computing Eigenvectors from Eigenvalues In an Arbitrary Orthonormal Basis [PDF]
arXiv, 2019 The method of computing eigenvectors from eigenvalues of submatrices can be shown as equivalent to a method of computing the constraint which achieves specified stationary values of a quadratic optimization. Similarly, we show computation of eigenvectors of an orthonormal basis projection using eigenvalues of sub-projections.
arxiv
APPLICATION OF THE RANDOM MATRIX THEORY ON THE CROSS-CORRELATION OF STOCK PRICES [PDF]
International Journal of Mathematical Modelling & Computations, 2016 The analysis of cross-correlations is extensively applied for understanding of interconnections in stock markets. Variety of methods are used in order to search stock cross-correlations including the Random Matrix Theory (RMT), the Principal Component ...
F. Sotoude Vanoliya +1 more
doaj
, 1997 The decomposition of a matrix A into a product of two or three matrices can (depending on the characteristics of those matrices) be a very useful first step in computing such things as the rank, the determinant, or an (ordinary or generalized) inverse (of A) as well as a solution to a linear system having A as its coefficient matrix.
openaire +3 more sources
Science Journal of University of Zakho, 2018 In this study the energy spectrum and Eigenvectors with a special type of central potential will be obtained by using Nikiforov-Uvarov method. The method covers a new algebraic technique to make an exact diagonalization to find the eigenvalues and ...
Aziz H. Rahim, Nzar R. Abdullah
doaj
Elliptic quantum curves of class S k $$ {\mathcal{S}}_k $$
Journal of High Energy Physics, 2021 Quantum curves arise from Seiberg-Witten curves associated to 4d N $$ \mathcal{N} $$ = 2 gauge theories by promoting coordinates to non-commutative operators.
Jin Chen +3 more
doaj +1 more source
Eigenvectors from eigenvalues revisited [PDF]
arXiv, 2019 This is a remark on a recent post by P. Denton, S. Parke, T. Tao, X.
arxiv
On the eigenstructure of the $(α,q)$-Bernstein operator [PDF]
arXiv, 2020 We obtain eigenvalues and eigenvectors of the $(\alpha,q)$-Bernstein operator $T_{n,q,\alpha}$. Moreover, we will give the limit behaviour of these eigenvalues and eigenvectors for all $q.$
arxiv