QR Factorization: Orthogonal Bases and Matrices

Related lectures (25)

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Explores matrix equivalence theorems for systems of equations and least squares solutions.

Covers Lyapunov exponents, chaos measurement, and perturbation analysis in dynamical systems.

Explores the uniqueness and properties of orthogonal projection, including decomposition, associated matrix, linearity, and practical examples.

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

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Covers the Gram-Schmidt process, QR decomposition, orthogonal projection theorem, and matrix formulas.

Covers the QR factorization of a matrix A into Q and R.

Explores symmetrical bilinear forms, the Pythagorean theorem, inequalities, and orthogonal matrices.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.