Abstract
The singular value decomposition (SVD), closely related to matrix eigenvalue-eigenvector decompositions, is a powerful tool for analyzing linear systems. Like all mathematical tools it has its legitimate uses, but it can also be abused, of which we will have more to say in Section 8.4.
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© 1990 Springer-Verlag New York Inc.
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Branham, R.L. (1990). The Singular Value Decomposition. In: Scientific Data Analysis. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3362-6_8
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DOI: https://doi.org/10.1007/978-1-4612-3362-6_8
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