Linear Algebra

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The property of invertibility

The property of diagonalizability

The property of similarity

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The trace is equal to the product of its eigenvalues

The trace is equal to the difference of its eigenvalues

The trace is equal to the maximum of its eigenvalues

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The sum of all elements in the matrix

The product of all elements in the matrix

The sum of elements on the off-diagonal of the matrix

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The study of the conditioning and regularization of linear systems with respect to quadratic semi-norms

The study of the conditioning and regularization of linear systems with respect to quadratic norms

The study of the conditioning and regularization of linear systems with respect to linear norms

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The GSVD decomposes a single matrix, while the SVD decomposes simultaneously a pair of matrices with the same number of columns

The GSVD decomposes simultaneously a pair of matrices with the same number of columns, while the SVD decomposes a single matrix

The GSVD and the SVD decompose a single matrix

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A matrix decomposition on a pair of matrices which generalizes the singular value decomposition

A matrix decomposition on a single matrix which generalizes the singular value decomposition

A matrix decomposition on a pair of matrices which generalizes the eigenvalue decomposition

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