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initial conditions for every TLS gradient flow, just like TLS EXIN, assures the
convergence.
Proposition 122 (Divergence Straight Line)
In every plane z
n
z
i
, the diver-
gence straight line is between the saddle/minimum and the maximum.
5.4.2 Analysis of Convergence for
p
<
n
In the case where
+
1) and all
v
n
+
1,
i
=
0,
i
=
p
+
1,
...
,
n
+
1, there are
n
−
p
+
1 critical points
going to infinity in the direction of the eigenvectors associated with the eigen-
values of the corresponding coincident asymptotes. Hence, there is an
n
−
p
+
1
divergence plane
spanned by these eigenvectors. The complementary subspace
(
nongeneric TLS subspace
)isthe(
p
−
1)-dimensional plane through the origin
and orthogonal to the divergence plane. All the reasonings about the case
p
=
n
are also valid here, just recalling that in this case, the lower saddle (minimum) cor-
responds to
σ
p
. In particular,
q
p
=
q
p
+
1
=···=
q
n
=
0. In the
space (MCA
vector space), the (
n
+
1)-dimensional vectors
v
p
+
1
,
...
,
v
n
+
1
are parallel to the
TLS hyperplane.
σ
> σ
=···=
σ
1
,
p
≤
n
(
σ
1
has multiplicity
n
−
p
p
p
+
1
n
+
n
+
5.4.3 Simulations
The first benchmark set of equations ([98, Ex. 3.1]) is
√
6
√
6
√
2
4
x
1
x
2
√
2
4
2
0
−
(5.128)
≈
−
√
3
√
2
2
√
2
2
v
3
=
[
√
2
/
2,
−
√
2
/
2, 0]
T
.
v
n
+
1,
n
+
1
=
v
3,3
=
0.
Here,
Note
that
The
solution
(using the SVD) is
1
√
6
,
T
1
√
6
x
=
(5.129)
being
x
T
;−
1
T
⊥
v
3
. All experiments with TLS EXIN and TLS GAO use a
constant learning rate equal to 0.05. Figure 5.16 shows the phase diagram of
TLS EXIN for different initial conditions: the red (black) initial conditions give
convergent (divergent) trajectories. The black straight line passing through the
red points contains the saddle/solution locus and coincides with the axis
z
1
.
The domain of convergence is given by the half-line with origin the maximum
(
−
1
.
2247,
−
1
.
2247)
and containing the saddle/solution
. All the nonconverging
trajectories tend to the divergence straight line (dark blue thick line), which is
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