Construction d'une méthode itérative II

Related lectures (30)

Page 3 of 3

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

Explores linear systems, covering direct and iterative methods for solving them with a focus on round-off errors and Richardson's algorithm.

Explores matrix inversion, pivoting, and iterative methods for solving linear systems of equations.

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

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

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

Covers the process of solving a linear system in numerical flow simulation using direct methods like Gaussian elimination and the TDMA algorithm.

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

Covers the Conjugate Gradient method for solving linear systems efficiently.

Covers the convergence of Newton's method and its applications in numerical analysis.