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We study lossy compression of a finite statement source generated in a fixed deductive environment. The source symbols are statements in a knowledge base endowed with a shared proof system, and reconstruction fidelity is measured by…

Information Theory · Computer Science 2026-05-29 Jianfeng Xu

Shaping codes are used to generate code sequences in which the symbols obey a prescribed probability distribution. They arise naturally in the context of source coding for noiseless channels with unequal symbol costs. Recently, shaping…

Information Theory · Computer Science 2022-05-10 Yi Liu , Yonglong Li , Pengfei Huang , Paul H. Siegel

This paper derives novel results on the characterization of the the causal information rate-distortion function (IRDF) $R_{c}^{it}(D)$ for arbitrarily-distributed one-sided stationary $\kappa$-th order Markov source x(1),x(2),.... It is…

Information Theory · Computer Science 2018-04-12 Milan S. Derpich , Marco A. Guerrero , Jan Østergaard

Service providers must encode a large volume of noisy videos to meet the demand for user-generated content (UGC) in online video-sharing platforms. However, low-quality UGC challenges conventional codecs based on rate-distortion…

Image and Video Processing · Electrical Eng. & Systems 2025-05-22 Samuel Fernández-Menduiña , Xin Xiong , Eduardo Pavez , Antonio Ortega , Neil Birkbeck , Balu Adsumilli

A computable expression for the rate-distortion (RD) function proposed by Heegard and Berger has eluded information theory for nearly three decades. Heegard and Berger's single-letter achievability bound is well known to be optimal for…

Information Theory · Computer Science 2012-12-12 Roy Timo , Tobias J. Oechtering , Michèle Wigger

The nascent field of Rate-Distortion-Perception (RDP) theory is seeing a surge of research interest due to the application of machine learning techniques in the area of lossy compression. The information RDP function characterizes the…

Information Theory · Computer Science 2023-05-01 Chunhui Chen , Xueyan Niu , Wenhao Ye , Shitong Wu , Bo Bai , Weichao Chen , Sian-Jheng Lin

This paper analyzes the joint Rate Distortion Function (RDF) of correlated multivariate Gaussian sources with individual square-error distortions. Leveraging Hotelling's canonical variable form, presented is a closed-form characterization…

Information Theory · Computer Science 2025-08-25 Evagoras Stylianou , Charalambos D. Charalambous , Themistoklis Charalambous

In this paper we consider the rate distortion problem of discrete-time, ergodic, and stationary sources with feed forward at the receiver. We derive a sequence of achievable and computable rates that converge to the feed-forward rate…

Information Theory · Computer Science 2011-06-07 Iddo Naiss , Haim Permuter

An encoder, subject to a rate constraint, wishes to describe a Gaussian source under squared error distortion. The decoder, besides receiving the encoder's description, also observes side information consisting of uncompressed source symbol…

Information Theory · Computer Science 2013-05-10 Chris T. K. Ng , Chao Tian , Andrea J. Goldsmith , Shlomo Shamai

In recent years, there has been a sharp increase in transmission of images to remote servers specifically for the purpose of computer vision. In many applications, such as surveillance, images are mostly transmitted for automated analysis,…

Computer Vision and Pattern Recognition · Computer Science 2022-09-26 Alon Harell , Anderson De Andrade , Ivan V. Bajic

In Sequential Massive Random Access (SMRA), a set of correlated sources is jointly encoded and stored on a server, and clients want to access to only a subset of the sources. Since the number of simultaneous clients can be huge, the server…

Information Theory · Computer Science 2018-01-18 Elsa Dupraz , Thomas Maugey , Aline Roumy , Michel Kieffer

We examine the coordinated and universal rate-efficient sampling of a subset of correlated discrete memoryless sources followed by lossy compression of the sampled sources. The goal is to reconstruct a predesignated subset of sources within…

Information Theory · Computer Science 2017-06-23 Vinay Praneeth Boda , Prakash Narayan

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

Despite a short history, neural image codecs have been shown to surpass classical image codecs in terms of rate-distortion performance. However, most of them suffer from significantly longer decoding times, which hinders the practical…

Image and Video Processing · Electrical Eng. & Systems 2023-05-16 Yixin Gao , Runsen Feng , Zongyu Guo , Zhibo Chen

In this paper, the rate-distortion theory of the Gray-Wyner lossy source coding system is investigated. For the case of jointly Gaussian distributed sources, we establish an expression for the rate-distortion function under the constraint…

Information Theory · Computer Science 2023-03-29 Guojun Chen , Yinfei Xu , Ling Liu , Tiecheng Song , Jing Hu

In this work we investigate the behavior of the minimal rate needed in order to guarantee a given probability that the distortion exceeds a prescribed threshold, at some fixed finite quantization block length. We show that the excess coding…

Information Theory · Computer Science 2011-02-15 Amir Ingber , Yuval Kochman

In the successive refinement problem, a fixed-length sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence. One of two reconstructions is obtained by…

Information Theory · Computer Science 2018-12-26 Tetsunao Matsuta , Tomohiko Uyematsu

A rate-distortion problem motivated by the consideration of semantic information is formulated and solved. The starting point is to model an information source as a pair consisting of an intrinsic state which is not observable,…

Information Theory · Computer Science 2021-05-11 Jiakun Liu , Wenyi Zhang , H. Vincent Poor

Motivated by questions in lossy data compression and by theoretical considerations, we examine the problem of estimating the rate-distortion function of an unknown (not necessarily discrete-valued) source from empirical data. Our focus is…

Information Theory · Computer Science 2013-01-18 M. T. Harrison , I. Kontoyiannis

We consider the variable-to-fixed length lossy source coding (VFSC) problem. The optimal compression rate of the average length of variable-to-fixed source coding, allowing a non-vanishing probability of excess-distortion $\varepsilon$, is…

Information Theory · Computer Science 2018-03-20 Lan V. Truong , Vincent Y. F. Tan