§Minor wording changes
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@ -578,7 +578,7 @@ The resulting formulation of the relaxed optimization problem is the following:%
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\end{subfigure}
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\caption{Visualization of the codeword polytope and the relaxed codeword
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polytope for an example code}
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polytope}
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\label{fig:dec:poly}
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\end{figure}%
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%
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@ -651,7 +651,7 @@ the so-called \textit{code-constraint polynomial} is introduced:%
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.\end{align*}%
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%
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The intention of this function is to provide a way to penalize vectors far
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from a codeword and favor those close to a codeword.
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from a codeword and favor those close to one.
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In order to achieve this, the polynomial is composed of two parts: one term
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representing the bipolar constraint, providing for a discrete solution of the
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continuous optimization problem, and one term representing the parity
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@ -781,7 +781,7 @@ it suffices to consider only proportionality instead of equality.}%
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&\propto \boldsymbol{x} - \boldsymbol{y}
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,\end{align*}%
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%
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Allowing equation \ref{eq:prox:step_log_likelihood} to be rewritten as%
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allowing equation \ref{eq:prox:step_log_likelihood} to be rewritten as%
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%
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\begin{align*}
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\boldsymbol{r} \leftarrow \boldsymbol{s}
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@ -823,6 +823,6 @@ return $\boldsymbol{\hat{c}}$
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\end{genericAlgorithm}
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\caption{Proximal decoding algorithm}
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\caption{Proximal decoding algorithm for an \ac{AWGN} channel}
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\label{fig:prox:alg}
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\end{figure}
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