Construction of an Iterative Method II

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Covers the Preconditioned Richardson Method for solving linear systems and the impact of preconditioning on convergence.

Newton's Method: Order 2

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

Direct and Iterative Methods for Linear Equations

Explores direct and iterative methods for solving linear equations, emphasizing symmetric matrices and computational cost.

Gradient Descent

Covers the concept of gradient descent in scalar cases, focusing on finding the minimum of a function by iteratively moving in the direction of the negative gradient.

Newton's Method: Convergence and Criteria

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

Nonlinearity: Methods and Examples

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

Effect of Rounding Errors in Linear Systems

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

Linear Systems: Iterative Methods

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

Iterative Solvers: Theory and Comparison

Explores solving linear systems iteratively and compares different solvers based on worst-case assumptions and convergence measures.

Iterative Methods

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