Jacobi Method: Part I

Related lectures (28)

Page 3 of 3

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Discusses eigenvalues, their calculation methods, and their applications in optimization and numerical analysis.

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

Covers the basics of numerical analysis and computational methods using Python, focusing on algorithms and practical applications in mathematics.

Explores nonlinearity in numerical flow simulation, covering linearization methods and practical examples.

Explores the Newton method for non-linear equations, discussing convergence criteria and stopping conditions.

Covers the Jacobi iterative method for solving electrostatic problems and discusses convergence and practical examples.

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