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Numerical Analysis. EE, NCKU Tien-Hao Chang (Darby Chang). In the previous slide. Error (motivation) Floating point number system difference to real number system problem of roundoff Introduced/propagated error Focus on numerical methods three bugs. About the exercise. In this slide.
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Numerical Analysis EE, NCKU Tien-Hao Chang (Darby Chang)
In the previous slide • Error (motivation) • Floating point number system • difference to real number system • problem of roundoff • Introduced/propagated error • Focus on numerical methods • three bugs
In this slide • Rootfinding • multiplicity • Bisection method • Intermediate Value Theorem • convergence measures • False position • yet another simple enclosure method • advantage and disadvantage in comparison with bisection method
Rootfinding Given a function , find a such that
Multiplicity for polynomials • For polynomials, multiplicity can be determined by factoring the polynomial • That’s easy, but
For non-polynomials • What about this , where • Clearly, , so the has a root at • But what is the multiplicity? • , but • the equation has a root of multiplicity 3at answer
For non-polynomials • What about this , where • Clearly, , so the has a root at • But what is the multiplicity? • , but • the equation has a root of multiplicity 3at
Rootfinding methods • 2 categories • simple enclosure methods • fixed point iteration schemes • Simple enclosure • bisection and false position • guaranteed to converge to a root, but slow • Fixed point iteration • Newton’s method and secant method • fast, but require stronger conditions to guarantee convergence
2.1 The Bisection Method
Bisection method • The most basic simple enclosure method • All simple enclosure methods are based on Intermediate Value Theorem
In Plain English • Find an interval of that the endpoints are opposite sign • Since one endpoint value is positive and the other negative, zero is somewhere between the values, that is, at least one root on that interval
Bisection method • The objective is to systematically shrink the size of that root enclosing interval • The simplest and most natural way is to cut the interval in half • Next is to determine which half contains a root • Intermediate Value Theorem, again • Repeat the process on that half
In action , and
You know what the bisection method is, but so far it is not an algorithm, why?
Note • The bisection method converges to a root of , not the root of • what’s the difference? • guarantees the existence of a root, but not uniqueness, and the bisection method converge to one of these roots • The bisection method cannot locate roots ofeven multiplicity(the sign does not change on either side of such roots) • is common to all simple enclosure techniques
http://www.dianadepasquale.com/ThinkingMonkey.jpg Rate of convergence, Order of convergence, and
Convergence measures • For any rootfinding technique, we have 3 convergence measures to construct the stopping condition • absolute error • relative error • test
Which is the Best? No one is always better than another answer
Which is the Best? No one is always better than another
Algorithm • Suppose that we decide to use the absolute error , but we don’t know the value of p • With the theorem, we can now construct an algorithm
Note • Performance measure • number of evaluations rather than number of iterations (could involve many floating point operations) • Underflow • both and will approaching zero • work with the signs rather than the sign of the product
Summary of bisection method • Advantage • straightforward • inexpensive (1 evaluation per iteration) • guarantee to converge • Disadvantage • error estimation can be overly pessimistic • (drawing for a extreme case of bisection method)
2.2 The Method of False Position
False position • Very similar to bisection method • Only differ in selecting
Selecting • False position uses more information • values of and • rather than just the signs