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Consider a pair of correlated Gaussian sources (X1,X2). Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear…

Information Theory · Computer Science 2007-07-25 D. Krithivasan , S. S. Pradhan

We consider a distributed source coding problem of $L$ correlated Gaussian observations $Y_i, i=1,2,...,L$. We assume that the random vector $Y^{L}={}^{\rm t} (Y_1,Y_2,$ $...,Y_L)$ is an observation of the Gaussian random vector…

Information Theory · Computer Science 2010-01-13 Yasutada Oohama

We extend quantum rate distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate distortion coding…

Quantum Physics · Physics 2013-12-09 Mark M. Wilde , Nilanjana Datta , Min-Hsiu Hsieh , Andreas Winter

We consider the problem of lossy source coding with a mismatched distortion measure. That is, we investigate what distortion guarantees can be made with respect to distortion measure $\tilde{\rho}$, for a source code designed such that it…

Information Theory · Computer Science 2008-04-07 Urs Niesen , Devavrat Shah , Gregory Wornell

For variable-length coding with an almost-sure distortion constraint, Zhang et al. show that for discrete sources the redundancy is upper bounded by $\log n/n$ and lower bounded (in most cases) by $\log n/(2n)$, ignoring lower order terms.…

Information Theory · Computer Science 2026-01-21 Sharang M. Sriramu , Aaron B. Wagner

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

We consider the problem of lossy source coding with side information under a privacy constraint that the reconstruction sequence at a decoder should be kept secret to a certain extent from another terminal such as an eavesdropper, a sender,…

Information Theory · Computer Science 2014-06-25 Kittipong Kittichokechai , Tobias J. Oechtering , Mikael Skoglund

This paper studies the performance of sparse regression codes for lossy compression with the squared-error distortion criterion. In a sparse regression code, codewords are linear combinations of subsets of columns of a design matrix. It is…

Information Theory · Computer Science 2017-07-17 Ramji Venkataramanan , Sekhar Tatikonda

We consider lossy source coding when side information affecting the distortion measure may be available at the encoder, decoder, both, or neither. For example, such distortion side information can model reliabilities for noisy measurements,…

Information Theory · Computer Science 2014-11-17 Emin Martinian , Gregory W. Wornell , Ram Zamir

Consider a source that produces independent copies of a triplet of jointly distributed random variables, $\{X_{i},Y_{i},Z_{i}\}_{i=1}^{\infty}$. The process $\{X_{i}\}$ is observed at the encoder, and is supposed to be reproduced at two…

Information Theory · Computer Science 2008-12-18 Alina Maor , Neri Merhav

A secrecy system with side information at the decoders is studied in the context of lossy source compression over a noiseless broadcast channel. The decoders have access to different side information sequences that are correlated with the…

Information Theory · Computer Science 2014-10-07 Eva C. Song , Paul Cuff , H. Vincent Poor

In this paper, we analyze the indirect source coding problem with side information at both the encoder and decoder, as well as only at the decoder. We first derive structural properties of the two rate distortion functions (RDFs) for…

Information Theory · Computer Science 2024-10-14 Evagoras Stylianou , Michail Gkagkos , Charalambos D. Charalambous

A distributed lossy compression network with $L$ encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean…

Information Theory · Computer Science 2022-06-06 Siyao Zhou , Sadaf Salehkalaibar , Jingjing Qian , Jun Chen , Wuxian Shi , Yiqun Ge , Wen Tong

A general method of source coding over expansion is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued source) to a set of much simpler problems, compressing discrete sources.…

Information Theory · Computer Science 2013-08-13 Hongbo Si , O. Ozan Koyluoglu , Sriram Vishwanath

The simplest example of a quantum information source with memory is a mixed source which emits signals entirely from one of two memoryless quantum sources with given a priori probabilities. Considering a mixed source consisting of a general…

Quantum Physics · Physics 2016-06-27 Felix Leditzky , Nilanjana Datta

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning problems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2024-05-24 Jiancheng Tang , Qianqian Yang , Deniz Gündüz

In this paper, we propose a local squared Wasserstein-2 (W_2) method to solve the inverse problem of reconstructing models with uncertain latent variables or parameters. A key advantage of our approach is that it does not require prior…

Machine Learning · Statistics 2024-06-12 Mingtao Xia , Qijing Shen

Integer-forcing source coding has been proposed as a low-complexity method for compression of distributed correlated Gaussian sources. In this scheme, each encoder quantizes its observation using the same fine lattice and reduces the result…

Information Theory · Computer Science 2019-06-05 Elad Domanovitz , Uri Erez

The problem of variable length and fixed-distortion universal source coding (or D-semifaithful source coding) for stationary and memoryless sources on countably infinite alphabets ($\infty$-alphabets) is addressed in this paper. The main…

Information Theory · Computer Science 2021-07-13 Jorge F. Silva , Pablo Piantanida

Randomized (dithered) quantization is a method capable of achieving white reconstruction error independent of the source. Dithered quantizers have traditionally been considered within their natural setting of uniform quantization. In this…

Information Theory · Computer Science 2017-04-26 Emrah Akyol , Kenneth Rose