lecture2_complete

lecture2_complete - tan(x) example. 4 The conditioning of a...

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CMPSC/MATH 451 Numerical Computations Lecture 2 Aug 24, 2011 Prof. Kamesh Madduri
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REVIEW True/False 2
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A problem is ill-conditioned if its solution is highly sensitive to small changes in problem data False . ill-conditioned problem => high condition number => relative change in solution >> relative change in input 3
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Using higher-precision arithmetic will make an ill- conditioned problem better conditioned False . Conditioning is a characteristic of the problem, not the algorithm. Recall the
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Unformatted text preview: tan(x) example. 4 The conditioning of a problem depends on the algorithm used to solve it • False . Same reason as previous question. 5 The choice of the algorithm has no effect on the propagated data error • True . It’s only affected by the variation in the data. 6 A stable algorithm applied to a well-conditioned problem necessarily produces an accurate solution. • True . Accurate solution = stable algorithm + well-conditioned problem 7...
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This note was uploaded on 01/19/2012 for the course CMPSC 451 taught by Professor Staff during the Spring '08 term at Penn State.

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lecture2_complete - tan(x) example. 4 The conditioning of a...

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