Error Analysis and Stability in Numerical Methods

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Numerical Analysis: Stability in ODEs

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

Thomas algorithm, accuracy of direct methods

Explores the Thomas algorithm for tridiagonal systems and the accuracy of direct methods in numerical computations.

Numerics: semester project

Covers the semester project on numerics, focusing on adaptive algorithms and multistep methods.

Vectorization in Python: Efficient Computation with Numpy

Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.

Advanced Numerical Analysis: Space Discretization

Explores advanced space discretization techniques in numerical analysis for solving differential systems efficiently and accurately.

Euler Forward Method

Introduces the Euler Forward Method for ODEs, focusing on error analysis and stability.

Iterative Numerical Methods: Convergence and Errors

Explores iterative numerical methods for solving equations, emphasizing convergence criteria, errors, and starting values' impact.

Nonlinear Equations: Methods and Applications

Covers methods for solving nonlinear equations, including bisection and Newton-Raphson methods, with a focus on convergence and error criteria.

Implicit Schemes in Numerical Analysis

Explores implicit schemes in numerical analysis, emphasizing stability and convergence properties in solving differential equations.

Numerical Methods: Iterative Techniques

Covers open methods, Newton-Raphson, and secant method for iterative solutions in numerical methods.