svd is here a sage command to reverse the SVD, that ia restore the original matrix?
SVD matrix analysis
SVD matrix analysis
Just make the product !
See the documentation of SVD of complex matrices:
sage: m = random_matrix(CDF,3)
sage: m.SVD?
You will read:
OUTPUT:
* U, S, V -- immutable matrices such that A =
U*S*V.conj().transpose() where U and V are orthogonal and S is
zero off of the diagonal.
So:
sage: m
[ 0.3310137301437883 + 0.5895210280973311*I 0.7988060507482333 + 0.001845004960518093*I 0.55953531271306 - 0.4157959932143387*I]
[ 0.31728704666930097 + 0.5252900028355088*I -0.8037722831442571 + 0.748001134324078*I 0.7570395959647946 + 0.8725543726416196*I]
[ 0.5889022178823824 + 0.8257326198637103*I -0.6730668617375402 - 0.17790861779943956*I -0.5589487514702225 - 0.4466254251771886*I]
sage: U, S, V = m.SVD()
sage: U
[ -0.284121544687194 + 0.39939285686891435*I 0.09804396065119658 + 0.4371298831463562*I 0.5260128510587949 + 0.5313902721050954*I]
[ -0.47799684194289516 - 0.6394302833691484*I 0.0839847095503589 + 0.3326361102951883*I 0.3181936443645485 - 0.3790785184872727*I]
[ 0.31925731509669564 - 0.1431188047985596*I 0.5908610195338464 + 0.5766176283510003*I -0.42684312329846164 + 0.11743972425625948*I]
sage: S
[ 2.014692905047209 0.0 0.0]
[ 0.0 1.4672457517786448 0.0]
[ 0.0 0.0 0.5578468204334117]
sage: V
[ -0.1371487984082707 0.8966597362597599 0.42094123635698283]
[ -0.2530085556355167 + 0.6671921582633321*I -0.16346409265449802 - 0.18004222519028812*I 0.2657659576982525 + 0.6008943651067534*I]
[ -0.674728237753376 + 0.1295118025530403*I -0.24594930656467023 + 0.2763594462509048*I 0.30406779436784737 - 0.5464848302324682*I]
sage: U*S*V.conjugate().transpose() == m
False
BUT, this is only because of numerical noise:
sage: (U*S*V.conjugate().transpose() - m).norm()
7.714272089062928e-16
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Asked: 2017-12-05 06:58:15 +0100
Seen: 341 times
Last updated: Dec 06 '17
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