Estimation Of Information In Parallel Gaussian Channels Via Model Order Selection
Carlos Alejandro Lopez, Ferran de Cabrera, Jaume Riba
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04 May 2020
We study the problem of estimating the overall mutual information in M independent parallel discrete-time memory-less Gaussian channels from N independent data sample pairs per channel (inputs and outputs). We focus on the case where the number of active channels L is sparse in comparison with the total number of channels (L<=4. The resulting improvement is shown in terms of the estimated information bias.
