MATH-251(a): Numerical analysis

Lectures in this course (53)

Covers Richardson's method for solving linear equations and its applications in system solutions and error control.

Covers the convergence analysis of iterative methods and the conditions for convergence.

Explores springs under forces using differential equations and mechanics examples.

Explores Richardson's methods for iterative linear system solutions and error control in symmetric positive definite systems.

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

Covers the retrograde Euler method, an implicit numerical scheme used to solve equations and the concept of convergence order.

Explores stability in ODEs, including error checks, equilibrium points, and global attractors, with a focus on numerical schemes like Euler's method.

Explores the Cauchy problem for ordinary differential equations and numerical methods using MATLAB.

Explores eigenvalues, stability, eigenvectors, and error estimation techniques in linear systems.

Explores methods for ordinary differential equations and the importance of Lipschitz continuity in ensuring unique solutions.

Explores error analysis in ordinary differential equations and convergence criteria for numerical methods.

Explores absolute stability in autonomous differential equation systems and the properties of equilibrium points and attractors.

Explores stability and control in ordinary differential equations, covering proof techniques and error control strategies.

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