The name is absent

Table 3.3: Performance of reduced model (here k_v = 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 k_υ = kf~) of HHA fork, N == 1501, as
compared with the full model.

k_v	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 ε₁ζ_cal = 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. Orientation discrimination in WS 2
2. IMMIGRATION AND AGRICULTURAL LABOR POLICIES
3. An alternative way to model merit good arguments
4. The name is absent
5. Innovation Policy and the Economy, Volume 11
6. ENERGY-RELATED INPUT DEMAND BY CROP PRODUCERS
7. Heterogeneity of Investors and Asset Pricing in a Risk-Value World
8. Income Taxation when Markets are Incomplete
9. Unilateral Actions the Case of International Environmental Problems
10. The name is absent