CISE301_Topic61 SE301: Numerical Methods Topic 6 Numerical Differentiation Lecture 23 KFUPM Read Chapter 23, Sections 1-2
CISE301_Topic62 L ecture 23 Numerical Differentiation First order derivatives High order derivatives Richardson Extrapolation Examples
CISE301_Topic63 Motivation How do you evaluate the derivative of a tabulated function. How do we determine the velocity and acceleration from tabulated measurements. Time (second) Displacement (meters)
CISE301_Topic64 Recall
CISE301_Topic65 Three Formula
CISE301_Topic66 The Three Formulas
CISE301_Topic67 Forward/Backward Difference Formula
CISE301_Topic68 Central Difference Formula
CISE301_Topic69 The Three Formula (Revisited)
CISE301_Topic610 Higher Order Formulas
CISE301_Topic611 Other Higher Order Formulas
Example Use forward, backward and centered difference approximations to estimate the first derivate of: f(x) = –0.1x 4 – 0.15x 3 – 0.5x 2 – 0.25x at x = 0.5 using step size h = 0.5 and h = 0.25 Note that the derivate can be obtained directly: f’(x) = –0.4x 3 – 0.45x 2 – 1.0x – 0.25 The true value of f’(0.5) = In this example, the function and its derivate are known. However, in general, only tabulated data might be given. CISE301_Topic612
Solution with Step Size = 0.5 f(0.5) = 0.925, f(0) = 1.2, f(1.0) = 0.2 Forward Divided Difference: f’(0.5) (0.2 – 0.925)/0.5 = | t | = |( )/ | = 58.9% Backward Divided Difference: f’(0.5) (0.925 – 1.2)/0.5 = | t | = |( )/ | = 39.7% Centered Divided Difference: f’(0.5) (0.2 – 1.2)/1.0 = -1.0 | t | = |( )/ | = 9.6% CISE301_Topic613
Solution with Step Size = 0.25 f(0.5)=0.925, f(0.25)=1.1035, f(0.75)= Forward Divided Difference: f’(0.5) ( – 0.925)/0.25 = | t | = |( )/ | = 26.5% Backward Divided Difference: f’(0.5) (0.925 – )/0.25 = | t | = |( )/ | = 21.7% Centered Divided Difference: f’(0.5) ( – )/0.5 = | t | = |( )/ | = 2.4% CISE301_Topic614
Discussion For both the Forward and Backward difference, the error is O(h) Halving the step size h approximately halves the error of the Forward and Backward differences The Centered difference approximation is more accurate than the Forward and Backward differences because the error is O(h 2 ) Halving the step size h approximately quarters the error of the Centered difference. CISE301_Topic615
CISE301_Topic616 Richardson Extrapolation
CISE301_Topic617 Richardson Extrapolation Use two derivate estimates to compute a third, more accurate approximation
Richardson Extrapolation Example Use the function: f(x) = –0.1x 4 – 0.15x 3 – 0.5x 2 – 0.25x Starting with h 1 = 0.5 and h 2 = 0.25, compute an improved estimate of f’(0.5) using Richardson Extrapolation Recall the true value of f’(0.5) = CISE301_Topic618
Solution The first-derivative estimates can be computed with centered differences as: CISE301_Topic619
CISE301_Topic620 Richardson Extrapolation Table D(0,0)=Φ(h) D(1,0)=Φ(h/2)D(1,1) D(2,0)=Φ(h/4)D(2,1)D(2,2) D(3,0)=Φ(h/8)D(3,1)D(3,2)D(3,3)
CISE301_Topic621 Richardson Extrapolation Table
CISE301_Topic622 Example
CISE301_Topic623 Example First Column
CISE301_Topic624 Example Richardson Table
CISE301_Topic625 Example Richardson Table This is the best estimate of the derivative of the function. All entries of the Richardson table are estimates of the derivative of the function. The first column are estimates using the central difference formula with different step size h.