Singular value decomposition
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix into a rotation, followed by a rescaling followed by another rotation. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any
Singular value decomposition - Wikipedia Jump to content From Wikipedia, the free encyclopedia Matrix decomposition This article includes a list of references , related reading , or external links , but its sources remain unclear because it lacks inline citations . Please help improve this article by introducing more precise citations. ( March 2026 ) ( Learn how and when to remove this message ) Illustration of the singular value decomposition UΣV * of a real 2 × 2 matrix M . Top: The action of M , indicated by its effect on the unit disc D and the two canonical unit vectors e 1 and e 2 . Left
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