Strong Data Processing Inequalities and $\Phi $ -Sobolev Inequalities for Discrete Channels

@article{Raginsky2016StrongDP,
  title={Strong Data Processing Inequalities and  \$\Phi \$ -Sobolev Inequalities for Discrete Channels},
  author={Maxim Raginsky},
  journal={IEEE Transactions on Information Theory},
  year={2016},
  volume={62},
  pages={3355-3389}
}
The noisiness of a channel can be measured by comparing suitable functionals of the input and output distributions. For instance, the worst case ratio of output relative entropy to input relative entropy for all possible pairs of input distributions is bounded from above by unity, by the data processing theorem. However, for a fixed reference input… CONTINUE READING

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