Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.
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Transcript of Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.
![Page 1: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/1.jpg)
Linear SystemsPivoting in Gaussian Elim.
CSE 541
Roger Crawfis
![Page 2: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/2.jpg)
The naïve implementation of Gaussian Elimination is not robust and can suffer from severe round-off errors due to:Dividing by zeroDividing by small numbers and adding.
Both can be solved with pivoting
Limitations of Gaussian Elimation
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What if at step i, Aii = 0?
Simple Fix:If Aii = 0
Find Aji 0 j > i
Swap Row j with i
Factored Portion
iiA
jiA
Row i
Row j
Partial Pivoting
![Page 4: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/4.jpg)
75
25.6
5.125.12
25.11025.1
2
14
x
x
Forward Elimination
52
1
5
4
1025.675
25.6
1025.15.120
25.11025.1
x
x
9999.4
0001.1
52
1
digitsx
x
Example – Partial Pivoting
![Page 5: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/5.jpg)
52
1
5
4
1025.6
25.6
1025.10
25.11025.1
x
x
Rounded to 3 digits
Example – Partial Pivoting
75
25.6
5.125.12
25.11025.1
2
14
x
x
Forward Elimination
52
1
5
4
1025.675
25.6
1025.15.120
25.11025.1
x
x
9999.4
0001.1
52
1
digitsx
x
5
0
32
1
digitsx
x
![Page 6: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/6.jpg)
Partial Pivoting to mitigate round-off error
Adds an O(n) search.
If | | < max | |
Swap row with arg (max | |)
ii jij i
ijj i
A A
i A
Avoids Small Multipliers
Better Pivoting
![Page 7: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/7.jpg)
Forward Elimination
5
2
1
5 107525.6
75
105.1225.10
5.125.12
x
x
5
1
32
1
digitsx
x
25.6
75
25.10
5.125.12
2
1
x
x
Rounded to 3 digits
75
25.6
5.125.12
25.11025.1
2
14
x
x
25.6
75
25.11025.1
5.125.12
2
14 x
x
swap
Partial Pivoting
![Page 8: Linear Systems Pivoting in Gaussian Elim. CSE 541 Roger Crawfis.](https://reader036.fdocuments.net/reader036/viewer/2022082816/56649d215503460f949f5f2d/html5/thumbnails/8.jpg)
Pivoting strategies
k
k
k
k
Partial Pivoting:Only row interchange
Complete (Full) PivotingRow and Column interchange
Threshold PivotingOnly if prospective pivot is found
to be smaller than a certain threshold
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Pivoting With Permutations
Adding permutation matrices in the mix:
However, in Gaussian Elimination we will only swap rows or columns below the current pivot point. This implies a global reordering of the equations will work:
bPMPMPMAxPMPMPM nnnnnnnn 112211112211
bxAM
MPbMPAx
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Pivoting
Again, the pivoting is strictly a function of the matrix A, so once we determine P it is trivial to apply it to many problems bk.
For LU factorization we have:LU = PALy = PbUx = y