Given an m x n matrix A, the Singular Value Decomposition is A = U * Sigma * V-transpose. Which correctly describes U, Sigma, and V-transpose?

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Answer

U and V are the same matrix when A is square and symmetric.

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U is an m x n matrix of eigenvalues, Sigma is m x m symmetric, and V is n x n lower triangular.

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Sigma contains the eigenvalues of A on its diagonal.

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U is m x m orthogonal (left singular vectors), Sigma is m x n diagonal with non-negative singular values, V-transpose is n x n orthogonal (right singular vectors transposed).

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Given an m x n matrix A, the Singular Value Decomposition is A = U * Sigma * V-t...

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