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MATH 577
http://amadeus.math.iit.edu/
~fass 1
3.2 The Secant Method
Recall Newton’s method
Main drawbacks:•requires coding of the derivative•requires evaluation of and in every iteration
Work-aroundApproximate derivative with difference quotient:
MATH 577
http://amadeus.math.iit.edu/
~fass 2
Secant Method
MATH 577
http://amadeus.math.iit.edu/
~fass 3
Graphical Interpretation
MATH 577
http://amadeus.math.iit.edu/
~fass 4
Graphical Interpretation
MATH 577
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~fass 5
Convergence Analysis
MATH 577
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~fass 6
Proof of Theorem 3.2
MATH 577
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~fass 7
Proof of Theorem 3.2 (cont.)
MATH 577
http://amadeus.math.iit.edu/
~fass 8
Proof of Theorem 3.2 (cont.)
MATH 577
http://amadeus.math.iit.edu/
~fass 9
Proof of Theorem 3.2 (cont.)
MATH 577
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~fass 10
Proof of Theorem 3.2 (cont.)earlier formula
MATH 577
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~fass 11
Proof of Theorem 3.2 (Exact order)
MATH 577
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~fass 12
Proof of Theorem 3.2 (Exact order)
(*):
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~fass 13
Proof of Theorem 3.2 (Exact order)
MATH 577
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~fass 14
Proof of Theorem 3.2 (Exact order)
(cf. Theorem)
MATH 577
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~fass 15
Comparison of Root Finding Methods
Other facts:•bisection method always converges•Newton’s method requires coding of derivative
MATH 577
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~fass 16
Newton vs. Secant (“Fair” Comparison)
MATH 577
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~fass 17
Generalizations of the Secant Method
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~fass 18
Müller’s Method
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~fass 19
Müller’s Method (cont.)
Features:•Can locate complex roots (even with real initial guesses)•Convergence rate =1.84•Explicit formula rather lengthy (can be derived with more knowledge on interpolation – see Chapter 6)