LEARNING OUTCOMES
You will learn to know the most common numerical methods and algorithms
You will understand the strenghts and weaknesses of these algorithms
You will be able to apply these algorithms using
self-made programs
numerical libraries
numerical programs.
CONTENT
Tools, computing environment in Kumpula, visualization
Basics of numerics: floating point numbers, error sources
Linear algebra: equations, decompositions, eigenvalue problems
Nonlinear equations: bisection, secant, Newton
Interpolation: polynomes, splines, Bezier curves
Numerical integration: trapeziodal, Romberg, Gauss
Function minimization: Newton, conjugate gradient, stochastic methods
Generation of random numbers: linear congruential, shift register, non-uniform random numbers
Statistical description of data: probability distributions, comparison of data sets
Modeling of data: linear and nonlinear fitting
Fourier and wavelet transformations: fast Fourier transform, discreet wavelet transform, applications
Differential equations: ordinary and partial differential equations
