Numerical Methods Contents - SAM
Numerical Methods Contents - SAM
Numerical Methods Contents - SAM
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The previous example (Code 2.8.14) showed that assembly of the Q-factor in the QR-factorization<br />
of A is not needed, when the linear system of equations Ax = b is to be solved by means of QRfactorization:<br />
the orthogonal transformations can simply be applied to the right hand side(s) whenever<br />
they are applied to the columns of A.<br />
Large (linear) electric circuit<br />
Sought:<br />
✄<br />
R1<br />
L<br />
C 1<br />
R 4<br />
R 2<br />
R 1<br />
C 1 R 1<br />
C 2<br />
R1<br />
L<br />
R 2<br />
C 2<br />
15 16 R 4 7 R 1<br />
17<br />
Discussion of Rem. 2.2.6 for QRfactorization:<br />
Inefficient (!) code<br />
✄<br />
Q ∈ R n,n dense matrix<br />
R ∈ R n,n dense matrix<br />
➣ O(n 2 ) computational effort for executing<br />
loop body<br />
1 % Setting: N ≫ 1,<br />
2 % large tridiagonal matrix A ∈ R n,n<br />
3 [Q,R] = qr (A) ;<br />
4 for j =1:N<br />
5 x = R \ ( Q’∗b) ;<br />
6 b = some_function ( x ) ;<br />
7 end<br />
Dependence of (certain) branch currents<br />
on “continuously varying” resistance<br />
R x<br />
(➣ currents for many different values of<br />
R x )<br />
R1<br />
C1<br />
R2<br />
8 18<br />
9 10<br />
L<br />
C2<br />
R3<br />
R4<br />
R x<br />
Fig. 26<br />
L<br />
R 2<br />
R 2 R2<br />
11 12 13 14<br />
Only a few entries of the nodal analysis matrix A (→ Ex. 2.0.1) are affected by variation of R x !<br />
(If R x connects nodes i & j ⇒ only entries a ii , a jj ,a ij , a ji of A depend on R x )<br />
R1<br />
C1<br />
R2<br />
C2<br />
R3<br />
R4<br />
U<br />
~<br />
Remedies:<br />
• Store R in sparse matrix format, see Code 2.8.14, Sect. 2.6.2.<br />
• Store Givens rotations contained in Q as array of triplets: G lk is coded as<br />
Ôº¾½¿ ¾º<br />
Repeating Gaussian elimination/LU-factorization for each value of R x from scratch seems<br />
wasteful.<br />
Ôº¾½ ¾º<br />
where rho (ˆ= ρ) is chosen as in Rem. 2.8.10.<br />
[l,k,rho] ,<br />
△<br />
Idea: • compute (sparse) LU-factorization of A once<br />
• Repeat:<br />
update LU-factors for modified A<br />
+<br />
(partial) forward and backward substitution<br />
Remark 2.8.17 (Testing for near singularity of a matrix).<br />
Very small (w.r.t. matrix norm) element r ii in QR-factor R ↔ A “nearly singular”<br />
△<br />
Problem: Efficient update of matrix factorizations in the case of ‘slight” changes of the matrix [18,<br />
Sect. 12.6], [38, Sect. 4.9].<br />
✸<br />
2.9.0.1 Rank-1-modifications<br />
2.9 ModificationTechniques<br />
Example 2.9.2 (Changing entries/rows/columns of a matrix).<br />
Example 2.9.1 (Resistance to currents map).<br />
Ôº¾½ ¾º<br />
Changing a single entry: given x ∈ K<br />
{<br />
A,Ã ∈ Kn,n a<br />
: ã ij = ij , if (i,j) ≠ (i ∗ , j ∗ ) ,<br />
x + a ij , if (i,j) = (i ∗ , j ∗ ) ,<br />
Ôº¾½ ¾º<br />
, i ∗ ,j ∗ ∈ {1, ...,n} . (2.9.1)