Lectures:
Errors in numerical computations
Solution of non-linear equations: fixed point theorem, Newton method
Iterative solution of systems of linear equations
Eigenvalues and eigenvectors
Interpolation: polynomial, trigonometric, spline
Approximation:least square method, Tchebyshev metod
Numerical differentiation and quadrature
Numerical solution of initial value problem for ordinary differential equations
Projects:
The aim of the projects is solution of practical problem using numerical methods and their comparison with exact solution.
Project solution:
Problem analysis and proposal of appropriate numerical solution
Numerical solution
Exact solution and comparison with numerical solution
Discussion and conlusions
Excercises:
Introduction to Matlab
Error estimation on examples, computing of computer epsilon
Roots separation of nonlinear equations. Solution of nonlinear equations using bisection method, fixed point iterations and Newton method. Conditions of convergence. Solutions of systems of non-linear equations.
Jacobi and Gauss-Seidel nad SOR methods for solution of systems of linear equations.
Solution of systems of linear equations using steepest descent method and conjugate gradient method. Preconditioning.
Methods for finding of characteristic polynomial. Power method for largest and smallest eigenvalues.
Similarity transformations, Jacobi method, Givens, Housholder and Lanczos methods.
Lagrange and Newton interpolating polynomial, piecewise linear and cubic spline functions.
Least square method and normal equations. Systems of orthogonal functions.
Numerical differentiations.
Numerical quadrature: Newton-Cotes and Gauss formulae.
Numerical solution of initial value problem for ordinary differntial equations: Euler method, Runge-Kutta method.
Errors in numerical computations
Solution of non-linear equations: fixed point theorem, Newton method
Iterative solution of systems of linear equations
Eigenvalues and eigenvectors
Interpolation: polynomial, trigonometric, spline
Approximation:least square method, Tchebyshev metod
Numerical differentiation and quadrature
Numerical solution of initial value problem for ordinary differential equations
Projects:
The aim of the projects is solution of practical problem using numerical methods and their comparison with exact solution.
Project solution:
Problem analysis and proposal of appropriate numerical solution
Numerical solution
Exact solution and comparison with numerical solution
Discussion and conlusions
Excercises:
Introduction to Matlab
Error estimation on examples, computing of computer epsilon
Roots separation of nonlinear equations. Solution of nonlinear equations using bisection method, fixed point iterations and Newton method. Conditions of convergence. Solutions of systems of non-linear equations.
Jacobi and Gauss-Seidel nad SOR methods for solution of systems of linear equations.
Solution of systems of linear equations using steepest descent method and conjugate gradient method. Preconditioning.
Methods for finding of characteristic polynomial. Power method for largest and smallest eigenvalues.
Similarity transformations, Jacobi method, Givens, Housholder and Lanczos methods.
Lagrange and Newton interpolating polynomial, piecewise linear and cubic spline functions.
Least square method and normal equations. Systems of orthogonal functions.
Numerical differentiations.
Numerical quadrature: Newton-Cotes and Gauss formulae.
Numerical solution of initial value problem for ordinary differntial equations: Euler method, Runge-Kutta method.