Search results
Results From The WOW.Com Content Network
An infinite set of vectors is linearly independent if every nonempty finite subset is linearly independent. Conversely, an infinite set of vectors is linearly dependent if it contains a finite subset that is linearly dependent, or equivalently, if some vector in the set is a linear combination of other vectors in the set.
In mathematics, the Wronskian of n differentiable functions is the determinant formed with the functions and their derivatives up to order n – 1.It was introduced in 1812 by the Polish mathematician Józef Wroński, and is used in the study of differential equations, where it can sometimes show the linear independence of a set of solutions.
For finite-dimensional real vectors in with the usual Euclidean dot product, the Gram matrix is =, where is a matrix whose columns are the vectors and is its transpose whose rows are the vectors . For complex vectors in C n {\displaystyle \mathbb {C} ^{n}} , G = V † V {\displaystyle G=V^{\dagger }V} , where V † {\displaystyle V^{\dagger ...
Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.
Consequently, there will be three linearly independent generalized eigenvectors; one each of ranks 3, 2 and 1. Since λ 1 {\displaystyle \lambda _{1}} corresponds to a single chain of three linearly independent generalized eigenvectors, we know that there is a generalized eigenvector x 3 {\displaystyle \mathbf {x} _{3}} of rank 3 corresponding ...
Since the columns of P must be linearly independent for P to be invertible, there exist n linearly independent eigenvectors of A. It then follows that the eigenvectors of A form a basis if and only if A is diagonalizable. A matrix that is not diagonalizable is said to be defective.
A singular value for which we can find two left (or right) singular vectors that are linearly independent is called degenerate. If u 1 {\displaystyle \mathbf {u} _{1}} and u 2 {\displaystyle \mathbf {u} _{2}} are two left-singular vectors which both correspond to the singular value σ, then any normalized linear combination of ...
A basis B of the LP is called dual-optimal if the solution = is an optimal solution to the dual linear program, that is, it minimizes . In general, a primal-optimal basis is not necessarily dual-optimal, and a dual-optimal basis is not necessarily primal-optimal (in fact, the solution of a primal-optimal basis may even be unfeasible for the ...