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Singular Value Decomposition

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[U,S,V] = SVD(A) calculates the singular value decomposition of $ (m\times n)$-matrix A. The diagonal entries of the returned $ (m\times n)$-matrix S consist of the square roots of the eigenvalues of $ A^tA$ in descending order. The columns of the unitary matrices U and V are eigenvectors of $ AA^t$ and $ A^tA$, resp. We have $ A=USV^t$, hence $ S=U^tAV$.
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  automatically generated 1/12/2007