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Secant%20Method

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If so, go back to step 1, else stop the algorithm. ... Use the Secant method of finding roots of equations to. Find the inverse of a = 2.5. ... – PowerPoint PPT presentation

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Title: Secant%20Method


1
Secant Method
  • Computer Engineering Majors
  • Authors Autar Kaw, Jai Paul
  • http//numericalmethods.eng.usf.edu
  • Transforming Numerical Methods Education for STEM
    Undergraduates

2
Secant Method http//numericalmethods.eng.u
sf.edu
3
Secant Method Derivation
Newtons Method
(1)
Approximate the derivative
(2)
Substituting Equation (2) into Equation (1) gives
the Secant method
Figure 1 Geometrical illustration of the
Newton-Raphson method.
4
Secant Method Derivation
The secant method can also be derived from
geometry
The Geometric Similar Triangles
can be written as
On rearranging, the secant method is given as
Figure 2 Geometrical representation of the
Secant method.
5
Algorithm for Secant Method
6
Step 1
Calculate the next estimate of the root from two
initial guesses
Find the absolute relative approximate error
7
Step 2
  • Find if the absolute relative approximate error
    is greater than the prespecified relative error
    tolerance.
  • If so, go back to step 1, else stop the
    algorithm.
  • Also check if the number of iterations has
    exceeded the maximum number of iterations.

8
Example 1
  • To find the inverse of a number a, one can use
    the equation

where x is the inverse of a.
  • Use the Secant method of finding roots of
    equations to
  • Find the inverse of a 2.5. Conduct three
    iterations to estimate the root of the above
    equation.
  • Find the absolute relative approximate error at
    the end of each iteration, and
  • The number of significant digits at least correct
    at the end of each iteration.

9
Example 1 Cont.
Solution
Figure 3 Graph of the function f(x).
10
Example 1 Cont.
Initial guesses
Iteration 1 The estimate of the root is
The absolute relative approximate error is
The number of significant digits at least correct
is 0.
Figure 4 Graph of the estimated root after
Iteration 1.
11
Example 1 Cont.
Iteration 2 The estimate of the root is
The absolute relative approximate error is
The number of significant digits at least correct
is 0.
Figure 5 Graph of the estimated root after
Iteration 2.
12
Example 1 Cont.
Iteration 3 The estimate of the root is
The absolute relative approximate error is
The number of significant digits at least correct
is 0.
Figure 6 Graph of the estimated root after
Iteration 3.
13
Advantages
  • Converges fast, if it converges
  • Requires two guesses that do not need to bracket
    the root

14
Drawbacks
Division by zero
15
Drawbacks (continued)
Root Jumping
16
Additional Resources
  • For all resources on this topic such as digital
    audiovisual lectures, primers, textbook chapters,
    multiple-choice tests, worksheets in MATLAB,
    MATHEMATICA, MathCad and MAPLE, blogs, related
    physical problems, please visit
  • http//numericalmethods.eng.usf.edu/topics/secant_
    method.html

17
  • THE END
  • http//numericalmethods.eng.usf.edu
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