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Truncation Errors and Taylor Series

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1 Truncation Errors and Taylor Series
The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Chapter 4 Truncation Errors and Taylor Series

2 Introduction Truncation errors
Result when approximations are used to represent exact mathematical procedure For example:

3 Taylor Series - Definition
Mathematical Formulation used widely in numerical methods to express functions in an approximate fashion……. Taylor Series. It is of great value in the study of numerical methods. It provides means to predict a functional value at one point in terms of: - the function value - its derivatives at another point

4 Taylor’s Theorem General Expression
Where: Rn is the remainder term to account for all terms from n+1 to infinity. And is a value of x that lies somewhere between xi and xi+1

5 Taylor’s Theorem Any smooth function can be approximated as a polynomial Zero- order approximation: only true if xi+1 and xi are very close to each other. First- order approximation: in form of a straight line Second- order approximation:

6 Taylor’s Theorem - Remainder Term
Remainder Term: What is ξ ? If Zero- order approximation:

7 Taylor Series - Example
Use zero-order to fourth-order Taylor series expansions to approximate the function. f(x)= -0.1x4 – 0.15x3 – 0.5x2 – 0.25x +1.2 From xi = 0 with h =1. Predict the function’s value at xi+1 =1. Solution f(xi)= f(0)= 1.2 , f(xi+1)= f(1) = 0.2 ………exact solution Zero- order approx. (n=0)  f(xi+1)=1.2 Et = 0.2 – 1.2 = -1.0 First- order approx. (n=1)  f(xi+1)= 0.95 f(x)= -0.4x3 – 0.45x2 – x – 0.25, f’(0)= -0.25 f( xi+1)= h = 0.95 Et = = -0.75

8 Taylor Series - Example
Second- order approximation (n=2)  f(xi+1)= 0.45 f’’(x) = -1.2 x2 – 0.9x -1 , f’’(0)= -1 f( xi+1)= h h2 = 0.45 Et = 0.2 – 0.45 = -0.25 Third-order approximation (n=3)  f(xi+1)= 0.3 f( xi+1)= h h2 – 0.15h3 = 0.3 Et = 0.2 – 0.3 = -0.1

9 Taylor Series - Example
Fourth-order approximation (n = 4)  f(xi+1)= 0.2 f( xi+1)= h h2 – 0.15h3 – 0.1h 4= 0.2 Et = 0.2 – 0.2 = 0 The remainder term (R4) = 0 because the fifth derivative of the fourth-order polynomial is zero.

10 Approximation using Taylor Series Expansion
The nth-order Approximation

11 Taylor Series In General, the n-th order Taylor Series will be exact for n-th order polynomial. For other differentiable and continuous functions, such as exponentials and sinusoids, a finite number of terms will not yield an exact estimate. Each additional term will contribute some improvement. (see example 4.2)

12 Taylor Series Truncation error is decreased by addition of terms to the Taylor series. If h is sufficiently small, only a few terms may be required to obtain an approximation close enough to the actual value for practical purposes.








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