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Andreas Tsouchlos 2023-04-07 11:16:37 +02:00
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latex/thesis/chapters/analysis_of_results.tex
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@ -36,7 +36,7 @@
In this section, some similarities between the proximal decoding algorithm In this section, some similarities between the proximal decoding algorithm
and \ac{LP} decoding using \ac{ADMM} are be pointed out. and \ac{LP} decoding using \ac{ADMM} are be pointed out.
The two algorithms are compared and their different computational and decoding 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 \ac{ADMM} and the proximal gradient method can both be expressed in terms of
proximal operators. proximal operators.
@ -129,7 +129,7 @@ subjected to.
Their major differece is that while with proximal decoding the constraints Their major differece is that while with proximal decoding the constraints
are regarded in a global context, considering all parity checks at the same 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). considered separately, in a more local context (line 4 in both algorithms).
This difference means that while with proximal decoding the alternating This difference means that while with proximal decoding the alternating
minimization of the two parts of the objective function inevitably leads to minimization of the two parts of the objective function inevitably leads to