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10 −1
estimated spectrum
data variance
extrapolated spectrum
10 −2
10 −3
10 −4
10 −5
10 0
10 1
10 2
10 3
10 4
10 5
singular value index
Spectral Diagnostics from GCR. The estimated spectrum O . R /
Fig. 12.3
of the representer matrix
HBH T is shown by the dark solid line corresponding to the last GCR iterate (
R D
)in
Fig. 12.2 . Solid gray lines show O . R / based on iterates p D 10;20; and 40 , for comparison. The
data variance is ,where R D I . The extrapolated spectrum is computed from a linear fit to
.log.i/;log. i . R /// in the range p=4 i 3p=4
p D 58
due to the background and observations
may be obtained as diagnostic information from the GCR iterates. Substituting x p D
BH T x p in ( 12.4 ), one obtains
Finally, the two components of
J .
x p /
J . x p / D J B . x p / C J R . x p /
D x p
HBH T x p
(12.11)
HBH T x p y
/ T R 1 .
HBH T x p y
C .
/:
Because the GCR solver computes the residual r p at each iterate, one has
HBH T C R
.
/ x p D y r p :
(12.12)
Assuming that Rx p can be computed on demand, then
HBH T x p D y r p Rx p ;
(12.13)
and all terms in the expression for the objective function are computable. The
contribution from the background term is
J B .
x p / D . x p / T .
y r p Rx p /;
(12.14)
while the contribution from the observations is
J R .
r p C Rx p / T R 1 .
x p / D .
r p C Rx p /:
(12.15)
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