Eigenvectors & Eigenvalues Calculator

Characteristic value

Under the action of A transformation, vector ξ becomes only λ times in scale. ξ is A characteristic vector, λ is the corresponding eigenvalue (eigenvalue), is the quantity that can be measured (experimentally), and corresponding to the quantum mechanical theory, many quantities can not be measured, of course, other theoretical fields also have this phenomenon.

Let A isn order matrices exist where there is A constant number λ and A nonzero n-dimensional vector x such that Ax=λx, then lambda is said to be eigenvalues of matrices A where x is a belonging to the eigenvalues λ eigenvector.

Feature vector

In math, the eigenvector of the biometrics transform (eigenvector) is a non-degenerate vector whose direction does not change under the transform. The scale at which the vector scales under this transformation is called its eigenvalue. one biometrics transformation can usually be fully described by its eigenvalues and eigenvectors. Eigenspatial is an eigenvector Collection with the same eigenvalues. The word "characteristic" comes from the German eigen. It was first used in this sense by Hilbert in 1904, and earlier by Helmholtz in a related sense. The word eigen can be translated as "in itself", "specific to" , "characteristic", or "individual". This shows how important the eigenvalues are for defining a particular biometrics transformation.