Eigendecomposition of a matrix

In linear algebra, eigendecomposition (also known as eigenvalue decomposition or EVD) is a factorization of a matrix A {\displaystyle A} into a canonical form given by ⁠ A = V D V T {\displaystyle A=VDV^{\mathsf {T}}} ⁠, where D {\displaystyle D} is a diagonal matrix containing the eigenvalues of A {\displaystyle A} on the diagonal, and V {\displaystyle V} is an orthogonal matrix whose columns are the corresponding eigenvectors of ⁠ A {\displaystyle A} ⁠. Only diagonalizable matrices can be factorized in this way.

Source: Wikipedia — Eigendecomposition of a matrix (CC BY-SA 4.0)