Numerical Differentiation - University of Utah
my.mech.utah.edu › ~pardyjak › me2040Numerical Differentiation Now, keep the f’’ term and write a forward TS about xi+2 Multiply (1) by 2 and subtract from (3): + = + + +⋅⋅ 2 ''( )4 ( ) ( ) '( )2 2 2 f x h f x f x f x h i i i i (3) 2 − 2f(xi+1)=2f(xi)+2f'(xi)h+f''(xi)h 2 f(xi+2)=f(xi)+2f'(xi)h+2f''(xi)h 2 f(xi+2)−2f(xi+1)=−f(xi)+f''(xi)h ( ) 2 ( ) ( ) ''( ) 2 2 1 O h h f x f x f x f x i i i i +
Chapter 9: Numerical Differentiation - Purdue University
www.cs.purdue.edu › homes › enhChapter 9: Numerical Differentiation Numerical Differentiation Formulation of equations for physical problems often involve derivatives (rate-of-change quantities, such as v elocity and acceleration). Numerical solution of such problems involves numerical evaluation of the derivatives. One method for numerically evaluating derivatives is to use Finite DIfferences:
5 Numerical Differentiation
www2.math.umd.edu › lecture-notes › differentiation-chapThe numerical differentiation formula, (5.9), then becomes f0(x k) = Xn j=0 f(x j)l0 j (x k)+ 1 (n+1)! f(n+1)(ξ x k) Y j=0 j6= k (x k −x j). (5.10) We refer to the formula (5.10) as a differentiation by interpolation algorithm. Example 5.1 We demonstrate how to use the differentiation by integration formula (5.10) in the case where n = 1 and k = 0.