maths.free › Numerical Methods
Numerical Methods
Root finding, approximation, numerical integration and error.
Fianarana
newton's method on x^2 - 2 from 1
Core
Numerical integration: trapezoid and Simpson
Approximating an integral from sampled values, with error bounds.
integrate e^(-x^2) dx from 0 to 1
Core
Interpolation and Taylor approximation
Fitting polynomials through points, and approximating functions near a centre.
taylor series of e^x
Core
Floating point and error
Why 0.1 + 0.2 ≠ 0.3 on a computer, and how error propagates.
0.1 + 0.2
Most equations have no closed form; numerical methods find answers to as many decimals as you like and, crucially, tell you how wrong they might be. Every iteration here is shown as a step.
Fianarana marobe
Finding roots
Integration and interpolation
Linear systems and ODEs
Error
Ny sasany amin'ireo lesona ireo dia nalaina avy amin'ny lahatsoratra misokatra: Wikipedia. Ny pejy tsirairay dia manome ny anaran'ny loharano sy ny fahazoan-dàlana.
Marika ampiasaina eto
Tsindrio ny marika iray mba hahitana ny famaritana feno, sary, ary ny dikan'ny litera tsirairay ao aminy.
Fanontaniana napetrak'ireo olona
Why not just solve exactly?
Most equations have no closed-form solution at all, and many that do are unusable in practice. A numerical method delivers as many correct digits as you need, and a good one tells you how many that is.
Why can Newton's method fail?
If it starts where the tangent is nearly flat it shoots far away; near a repeated root it slows to a crawl; and with several roots it may land on the wrong one. A bracketing method like bisection is slower but cannot fail.
Adikao na esory ao amin'ny pejy famahana ny olana: isaky ny dingana, sary iray, ny valinteny dia miafina mandra-pahafantaranao. _Soloy →
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