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july 20 2013 chapter 14 numerical dierentiation uri m ascher and chen greif department of computer science the university of british columbia ascher greif cs ubc ca slides for the ...

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                  July 20, 2013
         Chapter 14: Numerical Differentiation
              Uri M. Ascher and Chen Greif
             Department of Computer Science
             The University of British Columbia
                {ascher,greif}@cs.ubc.ca
                 Slides for the book
     AFirst Course in Numerical Methods (published by SIAM, 2011)
        http://www.ec-securehost.com/SIAM/CS07.html
                                                  Numerical Differentiation    Goals
                                                  Goals of this chapter
         • To develop useful formulas for approximating derivatives of a function f(x)
             at a point x = x0;
         • to understand the mild stability limitations of numerical differentiation;
         • *to see differentiation techniques in action in some more advanced
             applications.
 Uri Ascher & Chen Greif (UBC Computer Science)           AFirst Course in Numerical Methods                                  July 20, 2013      1 / 1
                                                  Numerical Differentiation    Outline
                                                                   Outline
         • Deriving formulas using Taylor series
         • Richardson extrapolation
         • Deriving formulas using polynomial interpolation
         • Roundoff and data errors
         • *Differentiation matrices
     *advanced
 Uri Ascher & Chen Greif (UBC Computer Science)           AFirst Course in Numerical Methods                                  July 20, 2013      2 / 1
                                                  Numerical Differentiation    Motivation
                                   What is numerical differentiation
         • Given a function f(x) that is differentiable in the vicinity of a point x , it is
                                                                                                                                      0
             often necessary to estimate the derivative f′(x) and higher derivatives using
             nearby values of f.
         • Example 1.2 in Chapter 1 provides a simple instance of numerical
             differentiation. Here we consider the more complete picture. For instance, we
             ask
                 • how to achieve more, higher order difference formulas in an easy and orderly
                     fashion?
                 • how to control or altogether avoid the strong cancellation error effect
                     demonstrated in Example 1.3?
             These and several other questions are considered here.
 Uri Ascher & Chen Greif (UBC Computer Science)           AFirst Course in Numerical Methods                                  July 20, 2013      3 / 1
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...July chapter numerical dierentiation uri m ascher and chen greif department of computer science the university british columbia cs ubc ca slides for book afirst course in methods published by siam http www ec securehost com html goals this to develop useful formulas approximating derivatives a function f x at point understand mild stability limitations see techniques action some more advanced applications outline deriving using taylor series richardson extrapolation polynomial interpolation roundo data errors matrices motivation what is given that dierentiable vicinity it often necessary estimate derivative higher nearby values example provides simple instance here we consider complete picture ask how achieve order dierence an easy orderly fashion control or altogether avoid strong cancellation error eect demonstrated these several other questions are considered...

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