= Eigendecomposition of a matrix
{wiki=Eigendecomposition_of_a_matrix}
Eigendecomposition is a fundamental concept in linear algebra that involves decomposing a square matrix into its eigenvalues and eigenvectors. Specifically, for a square matrix \\( A \\), the eigendecomposition is expressed in the following form: \\\[ A = V \\Lambda V^\{-1\} \\\] where: - \\( A \\) is the original \\( n \\times n \\) matrix. - \\( V \\) is a matrix whose columns are the eigenvectors of \\( A \\).
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