University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Continuity of mutual entropy in the limiting signal-to-noise ratio regimes

Continuity of mutual entropy in the limiting signal-to-noise ratio regimes

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Stochastic Processes in Communication Sciences

We 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 show how this can be used for a correct proof of the entropy-power inequality under various types of assumptions.

This talk is part of the Isaac Newton Institute Seminar Series series.

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