Fixed convergence figure
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@ -757,15 +757,14 @@ as the gradients of the negative log-likelihood and the code-constraint
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polynomial, which influence the next estimate.
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\begin{figure}[h]
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\begin{minipage}[c]{0.25\textwidth}
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}[scale = 0.35]
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -783,13 +782,17 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla L \right)_2$}
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\addlegendentry{$\left(\nabla h \right)_2 $}
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\end{axis}
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\end{tikzpicture}\\
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\begin{tikzpicture}[scale = 0.35]
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\end{tikzpicture}
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\end{subfigure}%
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\hfill
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -807,13 +810,17 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla L \right)_3$}
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\addlegendentry{$\left(\nabla h \right)_3 $}
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\end{axis}
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\end{tikzpicture}\\
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\begin{tikzpicture}[scale = 0.35]
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\end{tikzpicture}
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\end{subfigure}%
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -832,51 +839,16 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla h \right)_4 $}
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\end{axis}
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\end{tikzpicture}
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\end{minipage}%
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\begin{minipage}[c]{0.5\textwidth}
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\vspace*{-1cm}
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\end{subfigure}%
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\hfill
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}[scale = 0.85, spy using outlines={circle, magnification=6,
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connect spies}]
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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]
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\addplot [NavyBlue, mark=none, line width=1]
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table [col sep=comma, x=k, y=comb_r_s_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addplot [ForestGreen, mark=none, line width=1]
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table [col sep=comma, x=k, y=grad_L_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addplot [RedOrange, mark=none, line width=1]
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table [col sep=comma, x=k, y=grad_h_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addlegendentry{est}
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\addlegendentry{$\left(\nabla L \right)_1$}
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\addlegendentry{$\left(\nabla h \right)_1 $}
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\coordinate (spypoint) at (axis cs:100,0.53);
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\coordinate (magnifyglass) at (axis cs:175,2);
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\end{axis}
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\spy [black, size=2cm] on (spypoint)
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in node[fill=white] at (magnifyglass);
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\end{tikzpicture}
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\end{minipage}%
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\begin{minipage}[c]{0.25\textwidth}
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\centering
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\begin{tikzpicture}[scale = 0.35]
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -894,13 +866,17 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla L \right)_5$}
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\addlegendentry{$\left(\nabla h \right)_5 $}
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\end{axis}
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\end{tikzpicture}\\
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\begin{tikzpicture}[scale = 0.35]
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\end{tikzpicture}
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\end{subfigure}%
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -918,13 +894,17 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla L \right)_6$}
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\addlegendentry{$\left(\nabla h \right)_6 $}
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\end{axis}
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\end{tikzpicture}\\
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\begin{tikzpicture}[scale = 0.35]
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\end{tikzpicture}
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\end{subfigure}%
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\hfill
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\begin{subfigure}[t]{0.48\textwidth}
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\centering
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\begin{tikzpicture}
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=8cm,
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height=3cm,
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width=0.9\textwidth,
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height=0.3\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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@ -943,15 +923,51 @@ polynomial, which influence the next estimate.
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\addlegendentry{$\left(\nabla h \right)_7 $}
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\end{axis}
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\end{tikzpicture}
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\end{minipage}
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\end{subfigure}
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\caption{Internal variables of proximal decoder
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as a function of the number of iterations ($n=7$)\protect\footnotemark{}}
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\vspace{5mm}
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\begin{subfigure}[t]{\textwidth}
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\centering
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\begin{tikzpicture}[spy using outlines={circle, magnification=6,
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connect spies}]
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\begin{axis}[
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grid=both,
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xlabel={Iterations},
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width=0.6\textwidth,
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height=0.225\textwidth,
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scale only axis,
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xtick={0, 50, ..., 200},
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xticklabels={0, 25, ..., 100},
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]
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\addplot [NavyBlue, mark=none, line width=1]
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table [col sep=comma, x=k, y=comb_r_s_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addplot [ForestGreen, mark=none, line width=1]
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table [col sep=comma, x=k, y=grad_L_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addplot [RedOrange, mark=none, line width=1]
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table [col sep=comma, x=k, y=grad_h_0]
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{res/proximal/comp_bch_7_4_combined.csv};
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\addlegendentry{est}
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\addlegendentry{$\left(\nabla L \right)_1$}
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\addlegendentry{$\left(\nabla h \right)_1 $}
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\coordinate (spypoint) at (axis cs:100,1.11);
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\coordinate (magnifyglass) at (axis cs:-75,0);
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\end{axis}
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\spy [black, size=2cm] on (spypoint)
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in node[fill=white] at (magnifyglass);
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\end{tikzpicture}
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\end{subfigure}
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\caption{Visualization of a single decoding operation\protect\footnotemark{}
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for a code with $n=7$}
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\label{fig:prox:convergence}
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\end{figure}%
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%
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\footnotetext{A single decoding is shown, using the BCH$\left( 7,4 \right) $ code;
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$\gamma = 0.05, \omega = 0.05, E_b / N_0 = \SI{5}{dB}$
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\footnotetext{BCH$\left( 7,4 \right) $ code; $\gamma = 0.05, \omega = 0.05, K=200,
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\eta = 1.5, E_b / N_0 = \SI{5}{dB}$
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}%
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%
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\noindent It is evident that in all cases, past a certain number of
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@ -1146,7 +1162,8 @@ an invalid codeword.
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\end{figure}%
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%
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\footnotetext{(3,6) regular \ac{LDPC} code with n = 204, k = 102
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\cite[\text{204.33.484}]{mackay_enc}; $\gamma=0.05, \omega = 0.05, K=200, \eta=1.5$
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\cite[\text{204.33.484}]{mackay_enc}; $\gamma=0.05, \omega = 0.05, K=200, \eta=1.5,
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E_b / N_0 = \SI{5}{dB}$
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}%
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%
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