Singular value decomposition

Related lectures (28)

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Covers the analytical expression of orthogonal projections and reflections in 2D space.

Covers the concept of singular values in linear algebra and their properties, including diagonalization and practical examples.

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Explores spectral and singular value decompositions of matrices.

Covers the norm of a matrix, operator, singular values, and unitary matrices in linear algebra.

Explains Singular Value Decomposition, focusing on orthogonal vectors and matrix decomposition.

Explores architectural transformations optimizing area, time, and product in digital system design.

Covers the Singular Value Decomposition (SVD) of a matrix and its applications.

Explains the step-by-step process of finding the singular value decomposition of a matrix.

Explores Singular Value Decomposition theory, properties, uniqueness, matrix approximation, and dimensionality reduction applications.