Iterative Methods: Linear Systems

Related lectures (30)

Covers iterative methods for solving linear systems of equations and discusses the convergence properties of methods like Richardson's method.

Explores the Cholesky factorization method for symmetric positive definite matrices.

Covers the LU decomposition method applied to linear systems, presenting the system in two steps.

Explores the Thomas algorithm for tridiagonal systems and the accuracy of direct methods in numerical computations.

Covers the principles of regression and linear systems, focusing on iterative methods.

Introduces LU decomposition for efficient linear equation solving using matrix factorization.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.

Explores iterative methods for linear equations, including Jacobi and Gauss-Seidel methods, convergence criteria, and the conjugate gradient method.

Summarizes methods for resolving linear systems, including Gaussian elimination and LU decomposition.

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

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