Incremental Refinements and Multiple Descriptions With Feedback

نویسندگان

چکیده

It is well known that independent (separate) encoding of $K$ correlated sources may incur some rate loss compared to joint encoding, even if the decoding done jointly. This particularly evident in multiple descriptions problem, where it same source encoded each description. We observe under mild conditions about and distortion measure, sum-rate separately individually good tends rate-distortion function decoder limit vanishing small coding rates descriptions. Moreover, we then propose successively encode into round order achieve a final notation="LaTeX">$D$ after notation="LaTeX">$M$ rounds. provide two examples – Gaussian with mean-squared error an exponential one-sided for which excess vanishes as number rounds goes infinity, any fixed . result has interesting interpretation multi-round variant encoder gets (block) feedback regarding arrived: In infinity (i.e., many incremental rounds), total received approaches function. theoretical experimental evidence showing this phenomenon fact more general than above.

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ژورنال

عنوان ژورنال: IEEE Transactions on Information Theory

سال: 2022

ISSN: ['0018-9448', '1557-9654']

DOI: https://doi.org/10.1109/tit.2022.3176396