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