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Published November 2016 | Submitted
Journal Article Open

Nonasymptotic noisy lossy source coding

Abstract

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is asymptotically equivalent to a noiseless lossy source coding problem with a modified distortion function, nonasymptotically there is a noticeable gap in how fast their minimum achievable coding rates approach the common rate-distortion function, as evidenced both by the refined asymptotic analysis (dispersion) and the numerical results. The size of the gap between the dispersions of the noisy problem and the asymptotically equivalent noiseless problem depends on the stochastic variability of the channel through which the compressor observes the source.

Additional Information

© 2016 IEEE. Manuscript received November 13, 2013; revised December 18, 2014; accepted March 25, 2016. Date of publication May 3, 2016; date of current version October 18, 2016. This work was supported in part by the Division of Computing and Communication Foundations through the National Science Foundation under Grant CCF-1016625 and in part by the Division of Electrical, Communications and Cyber Systems through the Center for Science of Information, an NSF Science and Technology Center, under Grant CCF-0939370. This work was presented in part at the 2013 IEEE Information Theory Workshop.

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August 20, 2023
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October 20, 2023