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- W4300436505 abstract "In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain the target distortions at each decoding stage. In this paper, we derive a parametric characterization of the rate-distortion region for successive refinement of abstract sources. Our characterization extends Csiszar's result to successive refinement, and generalizes a result by Tuncel and Rose, applicable for finite alphabet sources, to abstract sources. This characterization spawns a family of outer bounds to the rate-distortion region. It also enables an iterative algorithm for computing the rate-distortion region, which generalizes Blahut's algorithm to successive refinement. Finally, it leads a new nonasymptotic converse bound. In all the scenarios where the dispersion is known, this bound is second-order optimal. In our proof technique, we avoid Karush-Kuhn-Tucker conditions of optimality, and we use basic tools of probability theory. We leverage the Donsker-Varadhan lemma for the minimization of relative entropy on abstract probability spaces." @default.
- W4300436505 created "2022-10-03" @default.
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- W4300436505 date "2017-07-29" @default.
- W4300436505 modified "2023-09-26" @default.
- W4300436505 title "Successive Refinement of Abstract Sources" @default.
- W4300436505 doi "https://doi.org/10.48550/arxiv.1707.09567" @default.
- W4300436505 hasPublicationYear "2017" @default.
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