|
Strength of drift noise (γ)
|
Algorithms
|
ε
M
|
ε
S
|
ε
F
|
|---|
| | |
Mean
|
STD
|
Mean
|
STD
|
Mean
|
STD
|
|
2.0
|
LS
|
9.18
|
3.63
|
0.47
|
0.10
|
41.38
|
14.19
|
| |
TLS
|
29.25
|
178.08
|
0.57
|
0.15
|
237.51
|
2995.95
|
| |
CTLS
|
8.37
|
3.95
|
0.51
|
0.12
|
40.28
|
20.33
|
|
1.0
|
LS
|
6.31
|
2.07
|
0.42
|
0.07
|
29.24
|
8.25
|
| |
TLS
|
8.21
|
5.02
|
0.48
|
0.11
|
41.76
|
28.25
|
| |
CTLS
|
5.01
|
2.00
|
0.43
|
0.09
|
24.67
|
9.62
|
|
0.1
|
LS
|
5.14
|
1.59
|
0.40
|
0.06
|
25.02
|
6.61
|
| |
TLS
|
6.21
|
2.38
|
0.45
|
0.09
|
32.87
|
15.91
|
| |
CTLS
|
3.79
|
1.40
|
0.40
|
0.05
|
19.71
|
6.89
|
|
0.05
|
LS
|
5.18
|
1.66
|
0.40
|
0.06
|
25.16
|
6.57
|
| |
TLS
|
6.20
|
2.39
|
0.45
|
0.09
|
32.29
|
15.30
|
| |
CTLS
|
3.79
|
1.46
|
0.40
|
0.06
|
19.56
|
6.80
|
- The table shows the error comparisons in terms of the mean and the standard deviation (STD) for different strengths of drift noise for each method based on 1000 Monte-Carlo simulations. The number of measurements per experiment is fixed at 12. All conditions are the same as in Table 1 with only the drift noise being added. ε
M
is the sum of two tems, i.e (1/N1) Σ |α
i j
| and (1/N2) Σ |β
i j
|, where β
i j
and β
i j
are the relative magnitude errors in the non-zero and zero elements of the true Jacobian, respectively, and N1 and N2 are the number of non-zero and zero elements in the true Jacobian, respectively. ε
S
is given by (1/n2) Σ |sign (
i j
) - sign(f
i j
)|, i.e. the average sign differences, where
i j
and f
i j
are the (i-th row, j-th column) elements of the estimated and the true Jacobian, respectively. ε
F
is the Frobenius norm of the difference between the estimated and the true Jacobian, i.e. || - F||
F
.
