Continuity of Mutual Entropy in the Limiting Signal-To-Noise Ratio Regimes

Mark Kelbert () and Yuri Suhov ()
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Mark Kelbert: Swansea University, Department of Mathematics
Yuri Suhov: University of Cambridge, Statistical Laboratory, DPMMS

A chapter in Stochastic Analysis 2010, 2011, pp 281-299 from Springer

Abstract: Abstract This article addresses the issue of the proof of the entropy power inequality (EPI), an important tool in the analysis of Gaussian channels of information transmission, proposed by Shannon. We analyse continuity properties of the mutual entropy of the input and output signals in an additive memoryless channel and discuss assumptions under which the entropy-power inequality holds true.

Keywords: Mutual entropy; Gaussian channel; Entropy power inequality (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-15358-7_14

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DOI: 10.1007/978-3-642-15358-7_14

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