Singular Value Decomposition: Theoretical Foundations

In course

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Description

This lecture covers the theoretical foundations of Singular Value Decomposition (SVD), explaining the decomposition of a matrix into singular values and vectors. It discusses the properties of symmetric matrices, eigenvalues, and eigenvectors, illustrating the SVD process step by step. The lecture also delves into the significance of SVD in linear algebra, emphasizing the exceptional cases and practical applications.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_qc95597s

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Ontological neighbourhood

Mathematics

Algebra: Linear algebra, Abstract algebra

Analysis: Tensor analysis

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