I am trying to prove some statements about singular value decomposition, but I am not sure what the difference between singular value and eigenvalue is.

Is “singular value” just another name for eigenvalue?

**Answer**

The singular values of a M×N matrix X are the square roots of the eigenvalues of the N×N matrix X∗X (where ∗ stands for the transpose-conjugate matrix if it has complex coefficients, or the transpose if it has real coefficients).

Thus, if X is N×N real symmetric matrix with non-negative eigenvalues, then eigenvalues and singular values coincide, but it is not generally the case!

**Attribution***Source : Link , Question Author : Ramon , Answer Author : The Phenotype*