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src/2024-12-03/presentation.tex

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+\documentclass[10pt, aspectratio=169, usenames, dvipsnames]{beamer}
+
+\usepackage{tikz}
+\usepackage{tikz-3dplot}
+\usetikzlibrary{spy, external, intersections}
+%\tikzexternalize[prefix=build/]
+
+\usepackage{pgfplots}
+\pgfplotsset{compat=newest}
+\usepgfplotslibrary{fillbetween}
+
+
+\usepackage{listings}
+\usepackage{subcaption}
+\usepackage{bbm}
+
+\usepackage{xcolor}
+\usepackage[outputdir=build/]{minted}
+\usemintedstyle{gruvbox-dark}
+
+\definecolor{gruvbox-bg}{HTML}{282828}
+
+
+%
+%
+% Custom commands
+%
+%
+
+
+\input{lib/latex-common/common.tex}
+\pgfplotsset{colorscheme/cel}
+
+%
+%
+% CEL Template
+%
+%
+
+
+\newcommand{\templates}{lib/cel-template}
+
+\input{\templates/packages.tex}
+\input{\templates/modifications.tex}
+\input{\templates/makros_own.tex}
+
+% % Change the way the overview is displayed
+% \AtBeginSection[]
+% {
+%     \begin{frame}[t]
+%         \frametitle{Overview}
+%     \tableofcontents[sectionstyle=show/shaded,
+%                      subsectionstyle=show/show/shaded,
+%                      subsubsectionstyle=hide]
+%     \end{frame}
+% }
+% \AtBeginSubsubsection[]{}
+% \AtBeginSubsection[]{}
+
+
+%
+%
+% Set up document
+%
+%
+
+
+\title{HiWi Notes: Minimize Code Constraint Polynomial using Adam}
+\subtitle{\small 03.12.2024}
+\author{\vspace{1.5mm} Andreas Tsouchlos}
+\date{ }
+
+\institute{Karlsruhe Institute of Technology (KIT), \\ Communications Engineering Lab (CEL) }
+
+\tikzstyle{every node}=[font=\small]
+\captionsetup[sub]{font=small}
+
+
+%
+%
+% Document body
+%
+%
+
+
+\begin{document}
+
+
+\begin{frame}[plain]
+	\maketitle
+\end{frame}
+
+\begin{frame}[t, fragile]
+    \frametitle{Implementation}
+    
+    \vspace*{-5mm}
+    \begin{minted}[
+        bgcolor=gruvbox-bg,  % Background color
+        fontsize=\small,     % Adjust font size
+        framesep=5mm,        % Frame separation
+        baselinestretch=1,   % Line spacing
+        breaklines,          % Allow line breaking
+        tabsize=4,           % Tab width
+    ]{python}
+def decode(self, y: torch.Tensor) -> torch.Tensor:
+    optimizer = torch.optim.Adam([y], lr=self._learning_rate)
+
+    c_hat = (y < 0).int()
+
+    for _ in range(self._K):
+        optimizer.zero_grad()
+        loss = self._code_constraint_polynomial(y)
+        loss.backward()
+        optimizer.step()
+
+        c_hat = (y < 0).int()
+
+        if not torch.any(torch.matmul(self._H, c_hat) % 2):
+            break
+
+    return c_hat
+    \end{minted}
+\end{frame}
+
+\begin{frame}[t]
+    \frametitle{Performance}
+
+    \begin{minipage}[t]{0.4\textwidth}
+        \begin{itemize}
+            \item Code: 204.33.484\citereference{Mac24}: (3,6) regular LDPC code
+            \item Decoder parameters
+                \begin{itemize}
+                    \item Learning Rate: $0.05$
+                    \item Max. Number of Adam optimizer iterations: $150$
+                \end{itemize}
+        \end{itemize}
+
+
+        \vspace{23mm}
+
+        \addreferences
+            {Mac24}{David J.C. MacKay: \emph{Encyclopedia of Sparse Graph Codes}.
+                Dec. 2024. url: \url{http://www.inference.org.uk/mackay/codes/data.html}}
+            {Hel+23}{Michael Helmling et al. \emph{Database of Channel Codes and ML Simulation Results.} Apr. 2023. url: \url{https://www.uni-kl.de/channel-codes}.}
+        \stopreferences
+    \end{minipage}%
+    \begin{minipage}[t]{0.6\textwidth}
+        \begin{figure}[H]
+            \centering
+
+            \begin{tikzpicture}
+                \begin{axis}[
+                    width=\textwidth,
+                    height=0.7\textwidth,
+                    ymode=log,
+                    xlabel={$E_\text{b}/N_0 (\text{dB})$},
+                    ylabel={FER (-\,-\,-), BER (---)},
+                    legend pos=south west,
+                    ytick={1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1},
+                    grid,
+                ]
+                    \addplot+[scol0, mark=none, line width=1pt, densely dashed, forget plot]
+                        table[col sep=comma, x=Eb_N0, y=FER]
+                            {res/performance_204.33.484.csv};
+                    \addplot+[scol0, mark=none, line width=1pt]
+                        table[col sep=comma, x=Eb_N0, y=BER]
+                            {res/performance_204.33.484.csv};
+                    \addlegendentry{Adam Decoder}
+
+                    \addplot+[scol2, mark=none, line width=1pt, densely dashed, forget plot]
+                        table[col sep=comma, x=Eb_N0, y=FER]
+                            {res/proximal_performance_204.33.484.csv};
+                    \addplot+[scol2, mark=none, line width=1pt]
+                        table[col sep=comma, x=Eb_N0, y=BER]
+                            {res/proximal_performance_204.33.484.csv};
+                    \addlegendentry{Proximal Decoder}
+
+                    \addplot+[black, mark=none, line width=1pt, densely dashed, forget plot]
+                        table[col sep=comma, x=Eb_N0, y=FER]
+                            {res/ml_performance_204.33.484.csv};
+                    \addlegendimage{black, mark=none, line width=1pt}
+                    \addlegendentry{ML Decoder\citereference{Hel+23}}
+                \end{axis}
+            \end{tikzpicture}
+        \end{figure}
+    \end{minipage}
+\end{frame}
+
+\begin{frame}[t]
+    \frametitle{Parameter Choice: Learning Rate}
+
+    \begin{minipage}[t]{0.4\textwidth}
+        \begin{itemize}
+            \item Code: 204.33.484\citereference{Mac24}: (3,6) regular LDPC code
+            \item Decoder parameters
+                \begin{itemize}
+                    \item $E_\text{b}/N_0 = 4 \text{dB}$
+                    \item Max. Number of Adam optimizer iterations: $150$
+                \end{itemize}
+            \vspace{5mm}
+            \item Chosen learning rate: $0.05$
+        \end{itemize}
+
+        \vspace{17mm}
+
+	    \addreference{\text{Mac24}}{David J.C. MacKay: \emph{Encyclopedia of Sparse Graph Codes}.
+	        December 2024. URL: \url{http://www.inference.org.uk/mackay/codes/data.html}}
+    \end{minipage}%
+    \begin{minipage}[t]{0.6\textwidth}
+        \begin{figure}[H]
+            \centering
+
+            \begin{tikzpicture}
+                \begin{axis}[
+                    width=\textwidth,
+                    height=0.7\textwidth,
+                    xlabel={Learning rate},
+                    ylabel={FER (-\,-\,-), BER (---)},
+                    ymode=log,
+                    grid,
+                ]
+                    \addplot+[scol0, mark=none, line width=1pt, densely dashed]
+                        table[col sep=comma, x=learning_rate, y=FER, discard if not={Eb_N0}{4.0}]
+                        {res/parameter_choice_learning_rate.csv};
+
+                    \addplot+[scol0, mark=none, line width=1pt]
+                        table[col sep=comma, x=learning_rate, y=BER, discard if not={Eb_N0}{4.0}]
+                        {res/parameter_choice_learning_rate.csv};
+
+                    \draw[scol1] (axis cs:5e-2,0.001) -- (axis cs:5e-2,2);
+                    \addplot[scol1, mark=*] coordinates {(5e-2,0.0074)} node{};
+                    \addplot[scol1, mark=*] coordinates {(5e-2,0.27)} node{};
+                \end{axis}
+            \end{tikzpicture}
+        \end{figure}
+    \end{minipage}
+\end{frame}
+
+\begin{frame}[t]
+    \frametitle{Parameter Choice: Max. Number of Iterations}
+
+    \begin{minipage}[t]{0.4\textwidth}
+        \begin{itemize}
+            \item Code: 204.33.484\citereference{Mac24}: (3,6) regular LDPC code
+            \item Decoder parameters
+                \begin{itemize}
+                    \item $E_\text{b}/N_0 = 4 \text{dB}$
+                    \item Learning rate: $0.05$
+                \end{itemize}
+            \vspace{5mm}
+            \item Chosen max. number of iterations: $150$
+        \end{itemize}
+
+        \vspace{23mm}
+
+	    \addreference{\text{Mac24}}{David J.C. MacKay: \emph{Encyclopedia of Sparse Graph Codes}.
+	        December 2024. URL: \url{http://www.inference.org.uk/mackay/codes/data.html}}
+    \end{minipage}%
+    \begin{minipage}[t]{0.6\textwidth}
+        \begin{figure}[H]
+            \centering
+
+            \begin{tikzpicture}
+                \begin{axis}[
+                    width=\textwidth,
+                    height=0.7\textwidth,
+                    xlabel={Maximum number of iterations of Adam optimizer},
+                    ylabel={FER (-\,-\,-), BER (---)},
+                    ymode=log,
+                    grid,
+                ]
+                    \addplot+[scol0, mark=none, line width=1pt, densely dashed]
+                        table[col sep=comma, x=max_iter, y=FER]
+                        {res/parameter_choice_max_iterations.csv};
+
+                    \addplot+[scol0, mark=none, line width=1pt]
+                        table[col sep=comma, x=max_iter, y=BER]
+                        {res/parameter_choice_max_iterations.csv};
+
+                    \draw[scol1] (axis cs:150,1e-3) -- (axis cs:150,2);
+                    \addplot[scol1, mark=*] coordinates {(150,0.0068)} node{};
+                    \addplot[scol1, mark=*] coordinates {(150,0.255)} node{};
+                \end{axis}
+            \end{tikzpicture}
+        \end{figure}
+    \end{minipage}
+\end{frame}
+
+\begin{frame}[t]
+    \frametitle{Comparison of Performance for Different Codes}
+    
+    \captionsetup[subfigure]{font=footnotesize}
+
+    \hspace*{-0.4cm}
+    \begin{minipage}[c]{0.9\textwidth}
+        \centering
+    
+        \begin{figure}[H]
+            \vspace*{-7mm}
+            \centering
+        
+            \begin{subfigure}[t]{0.5\textwidth}
+                \centering
+            
+                \begin{tikzpicture}[scale=0.8]
+                    \begin{axis}[
+                        grid=both,
+                        xlabel={$E_b / N_0$ (dB)},
+                        ylabel={FER (-\,-\,-), BER (---)},
+                        ymode=log,
+                        ymax=1.5, ymin=8e-5,
+                        width=0.9\textwidth,
+                        height=0.6\textwidth,
+                    ]
+                
+                        \addplot[scol0, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/performance_bch_31_26.csv};
+                        \addplot[scol0, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/performance_bch_31_26.csv};
+
+                        \addplot[scol2, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/proximal_performance_bch_31_26.csv};
+                        \addplot[scol2, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/proximal_performance_bch_31_26.csv};
+                    \end{axis}
+                \end{tikzpicture}
+            
+                \vspace*{-2mm}
+            
+                \caption{BCH code with $n=31, k=26$}
+            \end{subfigure}%
+            \begin{subfigure}[t]{0.5\textwidth}
+                \centering
+            
+                \begin{tikzpicture}[scale=0.8]
+                    \begin{axis}[
+                        grid=both,
+                        xlabel={$E_b / N_0$ (dB)},
+                        ylabel={FER (-\,-\,-), BER (---)},
+                        ymode=log,
+                        ymax=1.5, ymin=8e-5,
+                        width=0.9\textwidth,
+                        height=0.6\textwidth,
+                    ]
+
+                        \addplot[scol0, line width=1pt, solid, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/performance_96.33.965.csv};
+                        \addplot[scol0, line width=1pt, solid]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/performance_96.33.965.csv};
+
+                        \addplot[scol2, line width=1pt, solid, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/proximal_performance_96.33.965.csv};
+                        \addplot[scol2, line width=1pt, solid]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/proximal_performance_96.33.965.csv};
+                    \end{axis}
+                \end{tikzpicture}
+
+                \vspace*{-2mm}
+            
+                \caption{$\left( 3, 6 \right)$-regular LDPC code with $n=96, k=48$
+                    \citereference{Mac24, 96.33.965}}
+            \end{subfigure}%
+
+            \vspace*{-5mm}
+
+            \begin{subfigure}[t]{0.5\textwidth}
+                \centering
+            
+                \begin{tikzpicture}[scale=0.8]
+                    \begin{axis}[
+                        grid=both,
+                        xlabel={$E_b / N_0$ (dB)},
+                        ylabel={FER (-\,-\,-), BER (---)},
+                        ymode=log,
+                        ymax=1.5, ymin=8e-5,
+                        width=0.9\textwidth,
+                        height=0.6\textwidth,
+                    ]
+                
+                        \addplot[scol0, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma,
+                                    discard if gt={Eb_N0}{6}]
+                                {res/performance_204.33.484.csv};
+                        \addplot[scol0, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma,
+                                    discard if gt={Eb_N0}{6}]
+                                {res/performance_204.33.484.csv};
+
+                        \addplot[scol2, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma,
+                                    discard if gt={Eb_N0}{6}]
+                                {res/proximal_performance_204.33.484.csv};
+                        \addplot[scol2, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma,
+                                    discard if gt={Eb_N0}{6}]
+                                {res/proximal_performance_204.33.484.csv};
+                    \end{axis}
+                \end{tikzpicture}
+            
+                \vspace*{-2mm}
+            
+                \caption{$\left( 3, 6 \right)$-regular LDPC code with $n=204, k=102$
+                    \citereference{Mac24, 204.33.484}}
+            \end{subfigure}%
+            \begin{subfigure}[t]{0.5\textwidth}
+                \centering
+            
+                \begin{tikzpicture}[scale=0.8]
+                    \begin{axis}[
+                        grid=both,
+                        xlabel={$E_b / N_0$ (dB)},
+                        ylabel={FER (-\,-\,-), BER (---)},
+                        ymode=log,
+                        ymax=1.5, ymin=8e-5,
+                        width=0.9\textwidth,
+                        height=0.6\textwidth,
+                    ]
+                
+                        \addplot[scol0, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/performance_204.55.187.csv};
+                        \addplot[scol0, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/performance_204.55.187.csv};
+
+                        \addplot[scol2, line width=1pt, densely dashed]
+                            table [x=Eb_N0, y=FER, col sep=comma]
+                                {res/proximal_performance_204.55.187.csv};
+                        \addplot[scol2, line width=1pt]
+                            table [x=Eb_N0, y=BER, col sep=comma]
+                                {res/proximal_performance_204.55.187.csv};
+                    \end{axis}
+                \end{tikzpicture}
+            
+                \vspace*{-2mm}
+            
+                \caption{$\left( 5, 10 \right)$-regular LDPC code with $n=204, k=102$
+                    \citereference{Mac24, 204.55.187}}
+            \end{subfigure}%
+        \end{figure}
+    \end{minipage}%
+    \begin{minipage}[c]{0.1\textwidth}
+        \centering
+    
+        \begin{figure}
+            \centering
+            \vspace*{-1.2cm}
+            \hspace*{-2mm}
+            \begin{tikzpicture}[scale=0.8]
+                \begin{axis}[hide axis,
+                             xmin=10, xmax=50,
+                             ymin=0, ymax=0.4,
+                             legend columns=1,
+                             legend style={draw=white!15!black},
+                             legend cell align={left}]
+                    \addlegendimage{scol0, line width=1pt}
+                    \addlegendentry{Adam}
+
+                    \addlegendimage{scol2, line width=1pt}
+                    \addlegendentry{Proximal}
+                \end{axis}
+            \end{tikzpicture}
+        \end{figure}
+    \end{minipage}
+
+    \vspace*{-2mm}
+
+    \addreference{Mac24}{David J.C. MacKay: \emph{Encyclopedia of Sparse Graph Codes}.
+        Dec. 2024. url: \url{http://www.inference.org.uk/mackay/codes/data.html}.}
+\end{frame}
+
+
+\end{document}

src/2024-12-03/res/ml_performance_204.33.484.csv

@@ -0,0 +1,10 @@
+Eb_N0,FER,error_frames,total_frames
+1.00,1.193e-01,100,838
+1.50,4.002e-02,100,2499
+2.00,6.572e-03,100,15216
+2.50,6.019e-04,100,166127
+3.00,7.677e-05,100,1302564
+3.50,1.562e-05,100,6401819
+4.00,4.406e-06,100,22694922
+4.50,1.103e-06,100,90621994
+5.00,2.800e-07,28,100000000

src/2024-12-03/res/parameter_choice_learning_rate.csv

@@ -0,0 +1,218 @@
+# Simulation ended at 2024-12-02 18:28:36.698306
+# Duration: 571.28 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.33.484.alist
+#     SNR: [0.5, 6.0, 0.5]
+#     Learning rate: [0.01, 0.2, 0.01]
+#     Max iterations: 150
+Eb_N0,learning_rate,BER,FER,DFR,error_frames,total_frames
+0.5,0.01,0.1297794117647059,1.0,1.0,200,200
+0.5,0.02,0.1307107843137255,1.0,1.0,200,200
+0.5,0.03,0.1325735294117647,1.0,1.0,200,200
+0.5,0.04,0.1339950980392157,1.0,1.0,200,200
+0.5,0.05,0.1369607843137255,1.0,1.0,200,200
+0.5,0.060000000000000005,0.13980392156862745,1.0,1.0,200,200
+0.5,0.06999999999999999,0.14237745098039215,1.0,1.0,200,200
+0.5,0.08,0.14732843137254903,1.0,1.0,200,200
+0.5,0.09,0.15259803921568627,1.0,1.0,200,200
+0.5,0.09999999999999999,0.1568627450980392,1.0,1.0,200,200
+0.5,0.11,0.16095588235294117,1.0,1.0,200,200
+0.5,0.12,0.16715686274509803,1.0,1.0,200,200
+0.5,0.13,0.17276960784313725,1.0,1.0,200,200
+0.5,0.14,0.17875,1.0,1.0,200,200
+0.5,0.15000000000000002,0.1874264705882353,1.0,1.0,200,200
+0.5,0.16,0.1967156862745098,1.0,1.0,200,200
+0.5,0.17,0.2041421568627451,1.0,1.0,200,200
+0.5,0.18000000000000002,0.21384803921568626,1.0,1.0,200,200
+0.5,0.19,0.22389705882352942,1.0,1.0,200,200
+1.0,0.01,0.1082843137254902,1.0,1.0,200,200
+1.0,0.02,0.10740196078431373,1.0,1.0,200,200
+1.0,0.03,0.10872549019607843,1.0,1.0,200,200
+1.0,0.04,0.11024509803921569,1.0,1.0,200,200
+1.0,0.05,0.11213235294117647,1.0,1.0,200,200
+1.0,0.060000000000000005,0.1142156862745098,1.0,1.0,200,200
+1.0,0.06999999999999999,0.11656862745098039,1.0,1.0,200,200
+1.0,0.08,0.12022058823529412,1.0,1.0,200,200
+1.0,0.09,0.12372549019607842,1.0,1.0,200,200
+1.0,0.09999999999999999,0.12816176470588236,1.0,1.0,200,200
+1.0,0.11,0.13286764705882353,1.0,1.0,200,200
+1.0,0.12,0.13926470588235293,1.0,1.0,200,200
+1.0,0.13,0.14625,1.0,1.0,200,200
+1.0,0.14,0.14752450980392157,1.0,1.0,200,200
+1.0,0.15000000000000002,0.1558578431372549,1.0,1.0,200,200
+1.0,0.16,0.16473039215686275,1.0,1.0,200,200
+1.0,0.17,0.17401960784313725,1.0,1.0,200,200
+1.0,0.18000000000000002,0.1853186274509804,1.0,1.0,200,200
+1.0,0.19,0.19566176470588234,1.0,1.0,200,200
+1.5,0.01,0.08235294117647059,1.0,1.0,200,200
+1.5,0.02,0.0810652619256658,0.9950248756218906,0.9950248756218906,200,201
+1.5,0.03,0.08077368878585917,0.9852216748768473,0.9852216748768473,200,203
+1.5,0.04,0.0825847580411475,0.9852216748768473,0.9852216748768473,200,203
+1.5,0.05,0.08460066953610712,0.975609756097561,0.975609756097561,200,205
+1.5,0.060000000000000005,0.08644189383070301,0.975609756097561,0.975609756097561,200,205
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src/2024-12-03/res/parameter_choice_max_iterations.csv

@@ -0,0 +1,38 @@
+# Simulation ended at 2024-12-02 19:21:51.268599
+# Duration: 86.63 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.33.484.alist
+#     SNR: 4
+#     Learning rate: 0.05
+#     Max iterations: [10.0, 300.0, 10.0]
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src/2024-12-03/res/performance_204.33.484.csv

@@ -0,0 +1,39 @@
+# Simulation ended at 2024-12-02 18:58:17.471839
+# Duration: 1508.68 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.33.484.alist
+#     SNR: [0.5, 8.0, 0.25]
+#     Learning rate: 0.05
+#     Max iterations: 150
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.1306372549019608,1.0,1.0,100,100
+0.75,0.11980392156862744,1.0,1.0,100,100
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+7.75,1.3565357206492084e-06,8.514870369613492e-05,8.514870369613492e-05,100,1174416

src/2024-12-03/res/performance_204.55.187.csv

@@ -0,0 +1,21 @@
+# Simulation ended at 2024-12-03 00:07:32.466659
+# Duration: 112.99 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.55.187.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Learning rate: 0.05
+#     Max iterations: 150
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.15872549019607843,1.0,1.0,100,100
+1.0,0.14166666666666666,1.0,1.0,100,100
+1.5,0.12534313725490195,1.0,1.0,100,100
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+6.0,7.956671040509227e-05,0.004746084480303749,0.004746084480303749,100,21070

src/2024-12-03/res/performance_96.33.965.csv

@@ -0,0 +1,21 @@
+# Simulation ended at 2024-12-03 00:04:34.183699
+# Duration: 49.78 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/96.3.965.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Learning rate: 0.05
+#     Max iterations: 150
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.12830528846153846,0.9615384615384616,0.9615384615384616,100,104
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+6.0,0.00016164881794301878,0.00404122044857547,0.004000808244089715,100,24745

src/2024-12-03/res/performance_bch_31_26.csv

@@ -0,0 +1,21 @@
+# Simulation ended at 2024-12-03 00:05:13.843288
+# Duration: 7.79 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/BCH_31_26.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Learning rate: 0.05
+#     Max iterations: 150
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.09193548387096774,0.8333333333333334,0.625,100,120
+1.0,0.07633587786259542,0.7633587786259542,0.5877862595419847,100,131
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+6.0,0.0008577889839099581,0.016116035455278,0.012087026591458501,100,6205

src/2024-12-03/res/proximal_performance_204.33.484.csv

@@ -0,0 +1,41 @@
+# Simulation ended at 2024-12-02 23:05:29.898637
+# Duration: 457.69 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.33.484.alist
+#     SNR: [0.5, 8.0, 0.25]
+#     Omega: 0.05
+#     Gamma: 0.05
+#     Eta: 1.5
+#     Max iterations: 200
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.12,1.0,1.0,100,100
+0.75,0.10813434284604931,0.9900990099009901,0.9900990099009901,100,101
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+7.75,2.649929321490222e-07,1.7216101324331377e-05,1.7216101324331377e-05,100,5808516

src/2024-12-03/res/proximal_performance_204.55.187.csv

@@ -0,0 +1,23 @@
+# Simulation ended at 2024-12-03 00:09:39.594291
+# Duration: 13.34 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/204.55.187.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Omega: 0.05
+#     Gamma: 0.05
+#     Eta: 1.5
+#     Max iterations: 200
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.14955882352941177,1.0,1.0,100,100
+1.0,0.13053921568627452,1.0,1.0,100,100
+1.5,0.1117156862745098,1.0,1.0,100,100
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+6.0,2.1555362612449652e-05,0.001025010250102501,0.001025010250102501,100,97560

src/2024-12-03/res/proximal_performance_96.33.965.csv

@@ -0,0 +1,23 @@
+# Simulation ended at 2024-12-03 00:09:07.042779
+# Duration: 3.17 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/96.3.965.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Omega: 0.05
+#     Gamma: 0.05
+#     Eta: 1.5
+#     Max iterations: 200
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.12355324074074074,0.9259259259259259,0.9259259259259259,100,108
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+6.0,5.7918971359068664e-05,0.0014479742839767166,0.001390055312617648,100,69062

src/2024-12-03/res/proximal_performance_bch_31_26.csv

@@ -0,0 +1,23 @@
+# Simulation ended at 2024-12-03 00:09:16.332413
+# Duration: 0.22 seconds
+# Platform: Linux-6.6.63-1-lts-x86_64-with-glibc2.40
+# Parameters:
+#     Code: ../../codes/BCH_31_26.alist
+#     SNR: [0.5, 6.5, 0.5]
+#     Omega: 0.05
+#     Gamma: 0.05
+#     Eta: 1.5
+#     Max iterations: 200
+Eb_N0,BER,FER,DFR,error_frames,total_frames
+0.5,0.09201480698043363,0.819672131147541,0.5983606557377049,100,122
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