Biomedical Engineering Reference
In-Depth Information
Sensitivities can be retrieved by solving this set of equations for i D 1;2;:::;KC1.
In particular, for our working example we have
LJ
LJ
LJ
LJ
Ǜ
.j/
i
LJ
LJ
LJ
LJ
u
.j/
Z
.j/
i
.j/
D
J
R
DǛ
i
@
J
R
@
u
@
J
R
@Ǜ
i
D
C
D
.
u
d/
i
C
1
Ǜ
i
; iD1;2;:::;K
LJ
LJ
LJ
LJ
u
.j/
LJ
LJ
LJ
LJ
Ǜ
.j/
K
Z
.j/
K
C
1
.j/
D
J
R
D
@
J
R
@
u
@
J
R
@Ǜ
i
D
C
D
.
u
d/.
K
C
1
/ C
2
.
ref
/:
C
1
Notice that from the state equations (
6.30
), (
6.31
), we have for i D 1;2;:::;KC 1
LJ
LJ
LJ
LJ
u
.j/
.
i
/ D
i
C
b
r
i
C
i
C 3.
u
.j/
/
2
i
;
@
@
u
and
LJ
LJ
LJ
LJ
.j/
F
@Ǜ
i
@
Df
i
;iD 1;2;:::;K
LJ
LJ
LJ
LJ
.j/
@
@
D
u
.j/
:
Then, the
sensitivities equations
read
8
<
i
C
b
r
i
C
i
C 3.
u
.j/
/
2
i
D f
i
in
K
C
1
C
b
r
K
C
1
C
K
C
1
C 3.
u
.j/
/
2
K
C
1
D
u
.j/
(6.35)
in
:
i
D 0; i D 1;2;:::;KC 1
on :
Notice that these equations are linear in the sensitivities. Finally, we have
LJ
LJ
LJ
LJ
LJ
LJ
LJ
LJ
Z
Z
.j/
.j/
D
J
R
DǛ
i
D
J
R
D
.
u
.j/
d/
i
C
1
Ǜ
.j
i
;
.
u
.j/
d/
K
C
1
C
2
.j/
:
D
D
Gradients of the functional with respect to the control variables following this
approach requires therefore the solution of the K C 1 sensitivity equations.
Gradient Computation Through Adjoint Equations
In the following, we omit the iteration index j for simplicity. In the previous section
we computed the operator
@
LJ
LJ
LJ
LJ
u
@
u
applied to the sensitivities
i
. Let us consider the
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