maths.free › Numerical Methods › Interpolation and Taylor approximation
Interpolation and Taylor approximation
Fitting polynomials through points, and approximating functions near a centre.
Through n + 1 points passes exactly one polynomial of degree n (Lagrange). Near a point, the Taylor polynomial matches the derivatives. Picture it: the dashed polynomial hugging the curve near the centre and peeling away. Think it: approximation theory asks for the best polynomial over a whole interval, Chebyshev, not Taylor.
Жұмыстағы мысал · taylor series of e^x
Қадам сайын
- f(x) = e^{x}
Taylor series about x = 0: f(x) = Σ fᵏ(x₀)/k! · (x − x₀)ᵏ.
- f^{(0)}(0) = e^{x}\big|_{x=0} = 1
Derivative 0 at the centre.
- f^{(1)}(0) = e^{x}\big|_{x=0} = 1
Derivative 1 at the centre.
- f^{(2)}(0) = e^{x}\big|_{x=0} = 1
Derivative 2 at the centre.
- f^{(3)}(0) = e^{x}\big|_{x=0} = 1
Derivative 3 at the centre.
- f^{(4)}(0) = e^{x}\big|_{x=0} = 1
Derivative 4 at the centre.
- f^{(5)}(0) = e^{x}\big|_{x=0} = 1
Derivative 5 at the centre.
- \frac{x^{5}}{120} + \frac{x^{4}}{24} + \frac{x^{3}}{6} + \frac{x^{2}}{2} + x + 1
Assemble the terms up to degree 5.
Жауап беріңіз
Енді сен Мәтінді таңдап, жазу немесе өзіңіздің мәтініңізді салу. Әрбір қадамы сурет, сұрағанша жауап жасырылады.
Мұнда қолданылатын символдар
Тұтас анықтамасын, суретін және әрбір әріптің мағынасын көру үшін кез келген символды түртіңіз.
Не істеу керек: Interpolation and Taylor approximation
- Taylor series about x = 0: f(x) = Σ fᵏ(x₀)/k! · (x − x₀)ᵏ.
- Derivative 0 at the centre.
- Derivative 1 at the centre.
- Derivative 2 at the centre.
- Derivative 3 at the centre.
- Derivative 4 at the centre.
- Derivative 5 at the centre.
- Assemble the terms up to degree 5.
Адамдар қоятын сұрақтар
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.
Келесіде Numerical Methods
Root finding: bisection and Newton's methodNumerical integration: trapezoid and SimpsonFloating point and error