Singular Value Decomposition

In course

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Description

This lecture covers the Singular Value Decomposition (SVD) of a matrix, explaining how to decompose a matrix into three matrices, the properties of these matrices, and their applications. It also discusses the calculation of singular values, the construction of orthogonal vectors, and the importance of SVD in linear algebra.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_ew0kgwvn

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Ontological neighbourhood

Mathematics

Algebra: Linear algebra

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