Minor wording changes

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Andreas Tsouchlos 2023-04-07 11:16:37 +02:00
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In this section, some similarities between the proximal decoding algorithm
and \ac{LP} decoding using \ac{ADMM} are be pointed out.
The two algorithms are compared and their different computational and decoding
performance is explained on the basis of their theoretical structure.
performance is interpreted on the basis of their theoretical structure.
\ac{ADMM} and the proximal gradient method can both be expressed in terms of
proximal operators.
@ -129,7 +129,7 @@ subjected to.
Their major differece is that while with proximal decoding the constraints
are regarded in a global context, considering all parity checks at the same
time in the second step, with \ac{ADMM} each parity check is
time, with \ac{ADMM} each parity check is
considered separately, in a more local context (line 4 in both algorithms).
This difference means that while with proximal decoding the alternating
minimization of the two parts of the objective function inevitably leads to