Signless Laplacian matrixPrincipal eigenvectorSpectral radiusIn this paper, we study the entries of the principal eigenvector of the signless Laplacian matrix of a hypergraph. More precisely, we obtain bounds for this entries. These bounds are computed through other important parameters, such as ...
([119]). Let A=(aij)n×n be a nonnegative, irreducible matrix. Let si=∑j=1naij be the ith rowsum of A, and let △=maxisi and δ=minisi be the maximum and the minimum rowsums of A. If λ1 and x are the spectral radius and the principal eigenvector of A, then (2.15)x...
当新向量与原向量之间的夹角为 0^{\circ} 或180^{\circ} 时,原向量是eigenvector,n就是原向量的eigenvalue。 假设存在矩阵 A 、向量 \overrightarrow{vector_{in}} = \begin{bmatrix} 1 \\ 1 \end{bmatrix}、\overrightarrow{i}= \begin{bmatrix} 1 \\ 0 \\ \end{bmatrix} 和\overright...
Eigenvectors: Eigenvectors and Eigenvalues are in itself a big domain, let’s restrict ourselves to the knowledge of the same which we would require here. So, consider a non-zero vectorv. It is an eigenvector of a square matrixA, ifAvis a scalar multiple ofv. Or simply: Av = ƛv He...
Since H(ω) is a column vector, Y(ω)=Ps(ω)H(ω) is a column vector and matrix Y(ω)YH(ω) has rank 1. The eigen-decomposition of the correlation matrix is given by(14)Rxx(ω)=∑i=1Nλi(ω)qi(ω)qiH(ω)in which λi(ω) is eigenvalue and qi(ω) is corresponding ...
1.An eigenvalue of a graph is main if it has an eigenvector the sum of whose entries is not equal to zero, all trees with exactly two main eigenvalues have been characterized. 图的一个特征值称为主特征值,如果图有一个相应于该特征值的其各分量之和不为零的特征向量。 2.This paper determin...
(optional) equation(s) of the formoption=value Options • method: one of the nameseigenvectororsvd; controls if the principal component analysis uses the eigenvector method (on either the covariance or correlation matrix) or the singular values method. By default this is set tosvd. ...
The direction of PC1 is the eigenvector, and its magnitude is the eigenvalue. The angle of the x-axis to PC1 is the angle of rotation that is used in the transformation.First principal component An orthogonal line perpendicular to PC1 is calculated. This line is the second principal ...
matrix of ℓprincipal eigenvector \( {\tau}_{\alpha}^{spe} \) : threshold of SPE \( {\underset{\_}{x}}_j(k) \) : the lower bound (LB) H: feature space \( {\overline{x}}_j(k) \) : the upper bound (UL) a: mean of the SPE index b: variance of the SPE...
Except for the zero eigenvalue corresponding to the eigenvector ν(x), according to (25), they are called the principal curvatures of γ at x and are denoted by κi(x) for 1 ≤ i≤ n. The eigenvectors of W corresponding to the principal curvatures are called the principal directions. ...