Lecture

Singular Value Decomposition: Orthogonal Vectors and Matrix Decomposition

In course

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Description

This lecture covers the concept of Singular Value Decomposition (SVD) in linear algebra, focusing on the decomposition of a matrix into orthogonal vectors and the importance of singular values. It explains the process of constructing an orthonormal basis, determining singular values, and obtaining the SVD of a square matrix. The lecture also discusses the significance of unitary and orthogonal vectors in the decomposition process, along with practical examples and calculations.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_ocoj9ktt

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Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Analysis: Tensor analysis

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