Computation of Marton's Error Exponent for Discrete Memoryless Sources

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

The error exponent of fixed-length lossy source coding was established by Marton. Ahlswede showed that this exponent can be discontinuous at a rate R, depending on the probability distribution P of the given information source and the distortion measure d(x, y). The reason for the discontinuity in the error exponent is that there exists (d, ) such that the rate-distortion function R(|P) is neither concave nor quasi-concave with respect to P. Arimoto's algorithm for computing the error exponent in lossy source coding is based on Blahut's parametric representation of the error exponent. However, Blahut's parametric representation is a lower convex envelope of Marton's exponent, and the two do not generally agree. The contribution of this paper is to provide a parametric representation that perfectly matches the inverse function of Marton's exponent, thus avoiding the problem of the rate-distortion function being nonconvex with respect to P. The optimal distribution for fixed parameters can be obtained using Arimoto's algorithm. Performing a nonconvex optimization over the parameters successfully yields the inverse function of Marton's exponent.

本文言語英語
ホスト出版物のタイトル2023 IEEE International Symposium on Information Theory, ISIT 2023
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1372-1377
ページ数6
ISBN(電子版)9781665475549
DOI
出版ステータス出版済み - 2023
外部発表はい
イベント2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, 台湾
継続期間: 6月 25 20236月 30 2023

出版物シリーズ

名前IEEE International Symposium on Information Theory - Proceedings
2023-June
ISSN(印刷版)2157-8095

会議

会議2023 IEEE International Symposium on Information Theory, ISIT 2023
国/地域台湾
CityTaipei
Period6/25/236/30/23

!!!All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • 情報システム
  • モデリングとシミュレーション
  • 応用数学

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