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Unformatted text preview: >> vec2=vec(:,2) vec2 = -0.4994 -0.8664 >> sol2=A\vec2 sol2 = -0.0307 -0.0533 Note that in each case the solution is the eigenvector divided by the corresponding eigenvalue. Because the first eigenvalue is small and the second is large, the first solution is much higher than the second. So if we contaminate the second right hand side with a small fraction of the first >> vec2err=vec2+0.001*vec1 vec2err = -0.5004 -0.8665 We will not see much change in the right hand side, but we will see a very large change in the solution. >> sol2err=A\vec2err sol2err = -0.0495 -0.0555 The condition number of a matrix, which is a measure of the maximum amplification that can be expected when you change the data is indeed high here >> cond(A) ans = 474.3816...
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This note was uploaded on 03/27/2012 for the course EGM 3344 taught by Professor Raphaelhaftka during the Spring '09 term at University of Florida.
- Spring '09