Iterative Methods

Related lectures (30)

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Explores Jacobi, Gauss-Seidel, and SOR iterative methods for solving linear systems efficiently.

Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.

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

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

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

Covers iterative methods for solving linear equations and analyzing convergence, including error control and positive definite matrices.

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

Covers methods to solve nonlinear systems of equations in numerical analysis.

Explores the numerical analysis of nonlinear equations, focusing on convergence criteria and methods like bisection and fixed-point iteration.

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