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Related lectures (31)

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Advanced Analysis II: Matrices and Convergence

Covers the review of matrices convergence properties and eigenvalues in advanced analysis.

Convergence Analysis: Iterative Methods

Covers the convergence analysis of iterative methods and the conditions for convergence.

Inverse Power Method: Introduction to ODEs

Explores the inverse power method for ODEs and the significance of Lipschitz continuity.

Matrix Computations: Eigenvalues and Eigenvectors

Explores the complexity of matrix computations, focusing on eigenvalues and eigenvectors of symmetric matrices and the challenges in computing them.

Matrix Eigenvalues and Eigenvectors

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Linear Systems: Convergence and Methods

Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.

Symmetric Matrices: Eigenvalues and Eigenvectors

Explores the diagonalization of symmetric matrices using eigenvectors and eigenvalues, emphasizing orthogonality and real eigenvalues.

Power Method

Covers the Power Method for approximating the largest eigenvalue of a matrix.

Multivariate Statistics: Wishart and Hotelling T²

Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.

Matrices and Networks

Explores the application of matrices and eigendecompositions in networks.