Table 4.

The ability of 2C loop to buffer TF noise under of parameters in all three models.

Parameter values	Stop Model		Degr. Model		Dual Degr. Model
	$\overline{\epsilon }$	n	$\overline{\epsilon }$	n	$\overline{\epsilon }$	n
$\begin{array}{c}{h}_s=1\\ h_s=100\\ h_s=200\\ h_s=400\\ \end{array}$	$\begin{array}{c}\hfill -0.71\hfill \\ \hfill -0.49\hfill \\ \hfill -\mathbf{\text{0}}\mathbf{\text{.09}}\hfill \\ \hfill -0.30\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 34\hfill \\ \hfill 4\hfill \end{array}$	$\left\{\begin{array}{c}-0.69\hfill \\ -0.57\hfill \\ -0.57\hfill \\ -0.64\hfill \end{array}\right\}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.70\hfill \\ \hfill -0.63\hfill \\ \hfill \left\{\begin{array}{c}-0.57\hfill \\ -0.59\hfill \end{array}\right\}\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$
$\begin{array}{c}{k}_q=0.02\\ k_q=0.04\\ k_q=0.08\\ k_q=0.16\\ \end{array}$	$\begin{array}{c}\hfill -0.07\hfill \\ \hfill -0.17\hfill \\ \hfill -0.64\hfill \\ \hfill -0.94\hfill \end{array}$	$\begin{array}{c}\hfill 43\hfill \\ \hfill 26\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.38\hfill \\ \hfill -0.57\hfill \\ \hfill -0.75\hfill \\ \hfill -0.94\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.30\hfill \\ \hfill -0.58\hfill \\ \hfill -0.82\hfill \\ \hfill -0.94\hfill \end{array}$	$\begin{array}{c}\hfill 2\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$
$\begin{array}{c}{k}_s=0.01\\ k_s=0.25\\ k_s=0.50\\ k_s=0.75\\ \end{array}$	$\begin{array}{c}\hfill -0.69\hfill \\ \hfill -0.43\hfill \\ \hfill -0.13\hfill \\ \hfill 0.05\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 30\hfill \\ \hfill 55\hfill \end{array}$	$\begin{array}{c}\hfill -0.69\hfill \\ \hfill \left\{\begin{array}{c}-0.56\hfill \\ -0.58\hfill \\ -0.61\hfill \end{array}\right\}\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.69\hfill \\ \hfill -0.63\hfill \\ \hfill -0.59\hfill \\ \hfill -0.55\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$
$\begin{array}{c}{h}_p\left(h_g\right)=30;k_{rs}=1\cdot 10^{-5}\\ h_p\left(h_g\right)=60;k_{rs}=2\cdot 10^{-5}\\ h_p\left(h_g\right)=120;k_{rs}=4\cdot 10^{-5}\\ h_p\left(h_g\right)=240;k_{rs}=8\cdot 10^{-5}\\ \end{array}$	$\begin{array}{c}\hfill 0.07\hfill \\ \hfill -0.14\hfill \\ \hfill -0.42\hfill \\ \hfill -0.61\hfill \end{array}$	$\begin{array}{c}\hfill 58\hfill \\ \hfill 26\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.64\hfill \\ \hfill \left\{\begin{array}{c}-0.57\hfill \\ -0.56\hfill \end{array}\right\}\hfill \\ \hfill -0.64\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$	$\begin{array}{c}\hfill -0.63\hfill \\ \hfill -0.59\hfill \\ \hfill -0.49\hfill \\ \hfill -0.42\hfill \end{array}$	$\begin{array}{c}\hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \\ \hfill 0\hfill \end{array}$

For each model and for each parameter value we present the average ε value (left column) and the number n of experiments with positive value of this coefficient (right column). The method for calculation of ε is described in section. Negative ε mean that TF noise is dampen in a loop. The extremal ε values achieved at intermediate parameter values are shown in bold. The Wilcoxon Rank-Sum Test was used to test for significance of difference between the values of ε for adjacent parameter values. The differences which are statistically insignificant at the α = 0.05 level are placed in parentheses.