Numerical Analysis: Linear Systems

Related lectures (26)

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Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.

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

Explores eigenvalue problems, iterative methods, convergence properties, and applications in computational physics.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.

Explores the diagonalization of symmetric matrices through orthogonal decomposition and the spectral theorem.

Covers the stability analysis of ODEs using numerical methods and discusses stability conditions.

Explores the Jacobi method and diagonalization techniques, including similarity transformation, power methods, and QR decomposition.

Explains how to find free variables in matrix equations and analyze characteristic polynomials.

Covers tips on matrix construction and function manipulation using MATLAB.