Metric Mean Dimension and Analog Compression

Yonatan Gutman, Adam Śpiewak

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Wu and Verdú developed a theory of almost lossless analog compression, where one imposes various regularity conditions on the compressor and the decompressor with the input signal being modelled by a (typically infinite-entropy) stationary stochastic process. In this work we consider all stationary stochastic processes with trajectories in a prescribed set of (bi-)infinite sequences and find uniform lower and upper bounds for certain compression rates in terms of metric mean dimension and mean box dimension. An essential tool is the recent Lindenstrauss-Tsukamoto variational principle expressing metric mean dimension in terms of rate-distortion functions. We obtain also lower bounds on compression rates for a fixed stationary process in terms of the rate-distortion dimension rates and study several examples.

Original languageEnglish
Article number9086002
Pages (from-to)6977-6998
Number of pages22
JournalIEEE Transactions on Information Theory
Issue number11
StatePublished - Nov 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1963-2012 IEEE.


Manuscript received July 2, 2019; revised April 17, 2020; accepted April 25, 2020. Date of publication May 4, 2020; date of current version October 21, 2020. The work of Yonatan Gutman was supported in part by the National Science Center, Poland, under Grant 2013/08/A/ST1/00275 and Grant 2016/22/E/ST1/00448. The work of Adam S´piewak was supported by the National Science Center, Poland, under Grant 2016/22/E/ST1/00448. This article was presented in part at the 2019 IEEE International Symposium on Information Theory. (Corresponding author: Yonatan Gutman.) Yonatan Gutman is with the Institute of Mathematics, Polish Academy of Sciences, 00-656 Warszawa, Poland (e-mail: [email protected]).

FundersFunder number
National Science Center2013/08/A/ST1/00275, 2016/22/E/ST1/00448


    • analog signals
    • information dimension
    • lossless compression
    • metric mean dimension


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