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Explain the Singular Value Decomposition!
Given , a system
might be over- or under-determined. We still want to compute an approximate solution.
For any such , there exists the Singular Value Decomposition
where
is orthonormal:
is orthonormal:
From this, we can construct the pseudo-inverse
where
where
Due to numerical imprecisions, we use
Now, we can compute a solution:
This solution is
might be over- or under-determined. We still want to compute an approximate solution.
For any such , there exists the Singular Value Decomposition
where
is orthonormal:
is orthonormal:
From this, we can construct the pseudo-inverse
where
where
Due to numerical imprecisions, we use
Now, we can compute a solution:
This solution is
- a solution in the least-squares sense if M is overdetermined
- a solution in the last-norm sense if M in underdetermined
Karteninfo:
Autor: janisborn
Oberthema: Informatik
Thema: Computergrafik
Schule / Uni: RWTH Aachen
Ort: Aachen
Veröffentlicht: 18.05.2022