Numerical differentiation: finite differences
www.dam.brown.edu › people › alcyewis a second-order centered difference approximation of the sec-ond derivative f00(x). Here are some commonly used second- and fourth-order “finite difference” formulas for approximating first and second derivatives: O(∆x2) centered difference approximations: f0(x) : f(x+∆x)−f(x−∆x) /(2∆x) f00(x) : f(x+∆x)−2f(x)+f(x−∆x) /∆x2
THE SECOND-ORDER BACKWARD DIFFERENTIATION FORMULA IS ...
bionum.cs.purdue.edu › 89Skee146 R. D. Skeel / Second-order backward differentiation with stepsizes !rn := X,-X,+ The variable coefficient extension of the second-order BDF is given by Y, - (I+ &hJh,-r)Yn-r+ Wn/h#t-1)Yn-2 = 0 - &)V(%I~ YJ for n >, 2 where P” :=h,,/(h,-i +2h,), n>,l, and p0 := 0.
Backward differentiation formula - Wikipedia
en.wikipedia.org › wiki › Backward_differentiationThe backward differentiation formula is a family of implicit methods for the numerical integration of ordinary differential equations. They are linear multistep methods that, for a given function and time, approximate the derivative of that function using information from already computed time points, thereby increasing the accuracy of the approximation. These methods are especially used for the solution of stiff differential equations. The methods were first introduced by Charles F. Curtiss and
Backward differentiation formula - Wikipedia
https://en.wikipedia.org/wiki/Backward_differentiation_formulaThe backward differentiation formula (BDF) is a family of implicit methods for the numerical integration of ordinary differential equations. They are linear multistep methods that, for a given function and time, approximate the derivative of that function using information from already computed time points, thereby increasing the accuracy of the approximation. These methods are especially used for the solution of stiff differential equations. The methods were first introduced …
Finite difference - Wikipedia
en.wikipedia.org › wiki › Finite_differenceSecond order backward f ″ ( x ) ≈ ∇ h 2 [ f ] ( x ) h 2 = f ( x ) − f ( x − h ) h − f ( x − h ) − f ( x − 2 h ) h h = f ( x ) − 2 f ( x − h ) + f ( x − 2 h ) h 2 . {\displaystyle f''(x)\approx {\frac { abla _{h}^{2}[f](x)}{h^{2}}}={\frac {{\frac {f(x)-f(x-h)}{h}}-{\frac {f(x-h)-f(x-2h)}{h}}}{h}}={\frac {f(x)-2f(x-h)+f(x-2h)}{h^{2}}}.}