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*To find Singular Value Decomposition we have to follow the below rules:
*To find Singular Value Decomposition we have to follow the below rules:
*The left-singular vectors of the matrix M are a set of orthonormal eigenvectors of MM∗.
*The left-singular vectors of the matrix M are a set of orthonormal eigenvectors of MM∗.
*The right-singular vectors of M are a set of orthonormal eigenvectors of <math>M^∗M</math>.
*The right-singular vectors of M are a set of orthonormal eigenvectors of <math>M^{∗}M</math>.
*The non-zero singular values of M (found on the diagonal entries of Σ) are the square roots of the non-zero eigenvalues of both <math>M^∗M</math> and <math>MM^∗</math>.
*The non-zero singular values of M (found on the diagonal entries of Σ) are the square roots of the non-zero eigenvalues of both <math>M^∗M</math> and <math>MM^∗</math>.