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This paper studies the minimum achievable source coding rate as a function of blocklength $n$ and probability $\epsilon$ that the distortion exceeds a given level $d$. Tight general achievability and converse bounds are derived that hold at…

Information Theory · Computer Science 2016-11-15 Victoria Kostina , Sergio Verdú

We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that…

Information Theory · Computer Science 2025-09-16 Thomas Y. Chen

This paper focuses on the structural properties of test channels, of Wyner's operational information rate distortion function (RDF), $\overline{R}(\Delta_X)$, of a tuple of multivariate correlated, jointly independent and identically…

Information Theory · Computer Science 2020-11-24 Michail Gkagkos , Charalambos D. Charalambous

The rate-distortion saddle-point problem considered by Lapidoth (1997) consists in finding the minimum rate to compress an arbitrary ergodic source when one is constrained to use a random Gaussian codebook and minimum (Euclidean) distance…

Information Theory · Computer Science 2018-09-03 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We consider a remote source coding problem subject to a {distortion function}. Contrary to the use of the classical separable distortion criterion, herein we consider the more general, $f$-separable distortion measure and study its…

Information Theory · Computer Science 2023-05-19 Photios A. Stavrou , Yanina Shkel , Marios Kountouris

Rate-distortion formulation is the information-theoretic approach to the study of signal encoding systems. Since a more general approach to model the nonstationarity exhibited by real-world signals is to use appropriately fitted time…

Information Theory · Computer Science 2019-11-01 Jia-Chyi Wu

The amount of information lost in sub-Nyquist sampling of a continuous-time Gaussian stationary process is quantified. We consider a combined source coding and sub-Nyquist reconstruction problem in which the input to the encoder is a noisy…

Information Theory · Computer Science 2016-01-26 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar , Tsachy Weissman

Rate-distortion (R-D) function, a key quantity in information theory, characterizes the fundamental limit of how much a data source can be compressed subject to a fidelity criterion, by any compression algorithm. As researchers push for…

Information Theory · Computer Science 2022-03-14 Yibo Yang , Stephan Mandt

Consider the problem of estimating a latent signal from a lossy compressed version of the data when the compressor is agnostic to the relation between the signal and the data. This situation arises in a host of modern applications when data…

Information Theory · Computer Science 2021-01-12 Alon Kipnis , Stefano Rini , Andrea J. Goldsmith

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

We derive a simple general parametric representation of the rate-distortion function of a memoryless source, where both the rate and the distortion are given by integrals whose integrands include the minimum mean square error (MMSE) of the…

Information Theory · Computer Science 2010-04-30 Neri Merhav

We consider the problem of distributed lossy linear function computation in a tree network. We examine two cases: (i) data aggregation (only one sink node computes) and (ii) consensus (all nodes compute the same function). By quantifying…

Information Theory · Computer Science 2017-01-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

We consider the joint source-channel coding problem of sending a Gaussian source on a K-user Gaussian broadcast channel with bandwidth mismatch. A new outer bound to the achievable distortion region is derived using the technique of…

Information Theory · Computer Science 2010-11-22 Chao Tian , Suhas Diggavi , Shlomo Shamai

The relation between rate distortion function (RDF) and Bayesian filtering theory is discussed. The relation is established by imposing a causal or realizability constraint on the reconstruction conditional distribution of the RDF, leading…

Information Theory · Computer Science 2012-04-16 Photios A. Stavrou , Charalambos D. Charalambous , Christos K. Kourtellaris

In this work we study the rate-distortion function (RDF) for lossy compression of asynchronously-sampled continuous-time (CT) wide-sense cyclostationary (WSCS) Gaussian processes with memory. As the case of synchronous sampling, i.e., when…

Information Theory · Computer Science 2024-05-27 Zikun Tan , Ron Dabora , H. Vincent Poor

We derive a lower bound on the differential entropy of a log-concave random variable $X$ in terms of the $p$-th absolute moment of $X$. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds…

Information Theory · Computer Science 2018-04-04 Arnaud Marsiglietti , Victoria Kostina

Quantum random variable, distortion operator are introduced based on canonical operators. As the lower bound of rate distortion, the entanglement information rate distortion is achieved by Gaussian map for Gaussian source. General Gaussian…

Quantum Physics · Physics 2007-05-23 Xiao-yu Chen

We determine the rate region of the Gaussian scalar-help-vector source-coding problem under a covariance matrix distortion constraint. The rate region is achieved by a Gaussian achievable scheme. We introduce a novel outer bounding…

Information Theory · Computer Science 2010-01-27 Md Saifur Rahman , Aaron B. Wagner

We consider multiple description coding for the Gaussian source with K descriptions under the symmetric mean squared error distortion constraints, and provide an approximate characterization of the rate region. We show that the rate region…

Information Theory · Computer Science 2016-11-15 Chao Tian , Soheil Mohajer , Suhas N. Diggavi

In this paper, we introduce new lower bounds on the distortion of scalar fixed-rate codes for lossy compression with side information available at the receiver. These bounds are derived by presenting the relevant random variables as a…

Information Theory · Computer Science 2014-11-18 Avraham Reani , Neri Merhav