Eigenvalues & Eigenvectors 3x3 Matrices Calculator

matrices A =
Scalar quantity matrices (Z=c×I)=
|A| =
matrices A trace =
strangeness matrices (A - c×I) =
|A - c×I| =
Characteristic value c1 =
+ i
Characteristic value c2 =
+ i
Characteristic value c3 =
+ i
c1 in the feature vector (x, y, z) value =
c2 in the feature vector (x, y, z) value =
c3 in the feature vector (x, y, z) value =

Eigenvalues & Eigenvectors 3x3 Matrices Calculator:

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.