Matrix Inversion: Pivoting and Iterative Methods

Related lectures (30)

Page 3 of 3

Covers iterative methods for solving linear systems, emphasizing convergence analysis and well-chosen matrices.

Explores eigenvalues, eigenvectors, and methods for solving linear systems with a focus on rounding errors and preconditioning matrices.

Explores the effect of rounding errors in solving linear systems using the LU factorization method.

Covers the Gauss-Seidel method for solving linear systems iteratively with progressive substitution.

Introduces the Jacobi method for solving linear systems and determining convergence.

Explains Newton's method of order 2 for finding function zeros.

Explores the Jacobi method for linear systems, emphasizing convergence conditions and matrix properties.

Explores linear systems and iterative methods like gradient descent and conjugate gradient for efficient solutions.

Explores iterative methods for solving linear systems of equations, including Jacobi and Gauss-Seidel.

Explores iterative methods for solving nonlinear equations, discussing convergence properties and implementation details.