Lecture

Ill-posed Numerical Problems

Related lectures (28)

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

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.

Focuses on numerical modelling of atmospheric processes to predict weather and climate phenomena, covering key concepts and methods.

Explores backward and central differences for numerical differentiation, analyzing their properties and error analysis.

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

Covers Ordinary Differential Equations, first-order solutions, and numerical methods for IVP and BVP.

Discusses evaluation feedback, convergence, error analysis, and adaptive time steps in physics simulations.

Explores numerical methods for solving ODE systems, stability regions, and absolute stability importance.

Explores numerical methods in biomechanics for hip implants and emphasizes understanding conditions for improved designs and patient outcomes.

Covers exercises related to numerical methods, focusing on computational algorithms and problem-solving strategies.

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

Explores consistency and stability in numerical methods, emphasizing error analysis and the role of boundary conditions.

Covers the numerical approach to derivative calculation, focusing on formulas and methods such as fine differences.

Covers error analysis, stability, and adaptive time stepping in numerical methods, including convergence order and equilibrium points.

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

Covers the derivation of multi-group diffusion equations and the numerical methods for solving the neutron diffusion equation.

Explores the sensitivity of solutions in numerical methods, including linear systems and matrix norms, with an example of deblurring images.

Covers the implementation of numerical methods in MATLAB for solving chemical problems.

Covers derivation, integration, and simulation in Matlab, along with the representation of numbers and potential errors.