Numerical Methods: Exercises

Related lectures (25)

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

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

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

Covers numerical differentiation, forward differences, Taylor's expansion, Big O notation, and error minimization.

Covers the verification and validation process in numerical flow simulation, ensuring credibility of simulation outcomes.

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

Explores eigenvalue problems, iterative methods, convergence properties, and applications in computational physics.

Covers the stages of the explicit Runge-Kutta method for approximating y(t) with detailed explanations.

Covers the basics of computational geomechanics, including poroelasticity, plasticity, and numerical methods for solving geotechnical problems.

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