Strong Data Processing Constant is Achieved by Binary Inputs
Name
2020_binsdpi.pdf
Description
Accepted version
Size
211.82 KB
Format
Adobe PDF
Checksum (MD5)
021cde32b31c4c064d11fff2e411ed4b
Author(s)
Ordentlich, Or
Polyanskiy, Yury
Date Issued
2022
Journal
IEEE Transactions on Information Theory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Ordentlich, Or and Polyanskiy, Yury. 2022. "Strong Data Processing Constant is Achieved by Binary Inputs." IEEE Transactions on Information Theory, 68 (3).
Version
Author's final manuscript
Abstract
For any channel $P_{Y|X}$ the strong data processing constant is defined as
the smallest number $\eta_{KL}\in[0,1]$ such that $I(U;Y)\le \eta_{KL} I(U;X)$
holds for any Markov chain $U-X-Y$. It is shown that the value of $\eta_{KL}$
is given by that of the best binary-input subchannel of $P_{Y|X}$. The same
result holds for any $f$-divergence, verifying a conjecture of Cohen, Kemperman
and Zbaganu (1998).
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TIT.2021.3130189
