multiple eigenvalue
1Eigenvalue, eigenvector and eigenspace — In mathematics, given a linear transformation, an Audio|De eigenvector.ogg|eigenvector of that linear transformation is a nonzero vector which, when that transformation is applied to it, changes in length, but not direction. For each eigenvector… …
2Multiple time dimensions — The possibility that there might be more than one dimension of time has occasionally been discussed in physics and philosophy. Contents 1 Physics 2 Philosophy 3 In fiction 4 See also …
3Jacobi eigenvalue algorithm — The Jacobi eigenvalue algorithm is a numerical procedure for the calculation of all eigenvalues and eigenvectors of a real symmetric matrix. Description Let varphi in mathbb{R}, , 1 le k < l le n and let J(varphi, k, l) denote the n imes n matrix …
4Nash functions — In real algebraic geometry, a Nash function on an open semialgebraic subset U ⊂ Rn is an analytic function f: U → R satisfying a non trivial polynomial equation P(x,f(x)) = 0 for all x in U (A semialgebraic subset of Rn is a subset obtained from… …
5Vibration — For the soul music group, see The Vibrations. For the machining context, see Machining vibrations. For the albums, see Vibrations (Roy Ayers album) and Vibrations (The Three Sounds album). Classical mechanics …
6Eigenvalues and eigenvectors — For more specific information regarding the eigenvalues and eigenvectors of matrices, see Eigendecomposition of a matrix. In this shear mapping the red arrow changes direction but the blue arrow does not. Therefore the blue arrow is an… …
7Jordan normal form — In linear algebra, a Jordan normal form (often called Jordan canonical form)[1] of a linear operator on a finite dimensional vector space is an upper triangular matrix of a particular form called Jordan matrix, representing the operator on some… …
8List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra …
9Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …
10Matrix mechanics — Quantum mechanics Uncertainty principle …
