The name is absent



84

Table 3.3: Performance of reduced model (here kv = feʃ) of HH fork, N = 1501, as
compared with the full model. The first simulation set does not use Branch-Ortho for the
reduced system, while the next four sets use it, leading to far superior accuracy.

Speed-up

% Matched

% Mismatched

Γ

30, no Branch-Ortho

17.5×

349

Ï9?Ô

0.484

10

24.1×

63.4

18.7

0.707

15

22.5×

91.5

4.5

0.933

20

21.2x

94.3

1.5

0.963

30

17.5×

99.6

0

0.998

Table 3.4: Performance of reduced model (here kυ = kf~) of HHA fork, N == 1501, as
compared with the full model.

kv

Speed-up

% Matched

% Mismatched

Γ

20

23.5×

48.27

41.42

0.515

25

22.0×

85.87

0

0.924

30

19.7×

98.9

2.6

0.981

40

15.4×

100

0

1

kept the same, except in this case, we use εj,oca∣ = 10^4 and ε1ζcal = 10-51 and we
use 1000 random stimuli of between 0-250 pA. Note that the tolerances here are
not tuned to give the best performance, but rather have been chosen after just a
little experimentation to give good performance; it is possible that a better choice
may exist. Even though the spatially-varying A-type
K+ conductance necessitates a
slightly larger reduced system in order maintain the accuracy seen in the HH fork,
we still observe a similar speed-up, as Table 3.4 indicates.



More intriguing information

1. The name is absent
2. A Computational Model of Children's Semantic Memory
3. The name is absent
4. The Formation of Wenzhou Footwear Clusters: How Were the Entry Barriers Overcome?
5. The name is absent
6. Personal Experience: A Most Vicious and Limited Circle!? On the Role of Entrepreneurial Experience for Firm Survival
7. The name is absent
8. Estimation of marginal abatement costs for undesirable outputs in India's power generation sector: An output distance function approach.
9. The name is absent
10. The name is absent