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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

Rate distortion theory treats the problem of encoding a source with minimum codebook size while at the same time allowing for a certain amount of errors in the reconstruction measured by a fidelity criterion and distortion level. Similar to…

Information Theory · Computer Science 2025-11-13 Jonathan E. W. Huffmann , Holger Boche

The rate-distortion performance of neural image compression models has exceeded the state-of-the-art for non-learned codecs, but neural codecs are still far from widespread deployment and adoption. The largest obstacle is having efficient…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 David Minnen , Nick Johnston

We consider the lossy quantum source coding problem where the task is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel coding problems in the…

Quantum Physics · Physics 2023-02-02 Touheed Anwar Atif , Mohammad Aamir Sohail , S. Sandeep Pradhan

We consider a system in which two nodes take correlated measurements of a random source with time-varying and unknown statistics. The observations of the source at the first node are to be losslessly replicated with a given probability of…

Information Theory · Computer Science 2016-10-27 Fangzhou Chen , Bin Li , Can Emre Koksal

Consider a generalized multiterminal source coding system, where $\ell\choose m$ encoders, each observing a distinct size-$m$ subset of $\ell$ ($\ell\geq 2$) zero-mean unit-variance symmetrically correlated Gaussian sources with correlation…

Information Theory · Computer Science 2017-10-16 Jun Chen , Li Xie , Yameng Chang , Jia Wang , Yizhong Wang

We study variable-length feedback (VLF) codes under a strict delay constraint to maximize their average transmission rate (ATR) in a discrete memoryless channel (DMC) while considering periodic decoding attempts. We first derive a lower…

Information Theory · Computer Science 2015-02-25 Seong Hwan Kim , Dan Keun Sung , Tho Le-Ngoc

We consider the rate-limited quantum-to-classical optimal transport in terms of output-constrained rate-distortion coding for both finite-dimensional and continuous-variable quantum-to-classical systems with limited classical common…

Quantum Physics · Physics 2023-11-30 Hafez M. Garmaroudi , S. Sandeep Pradhan , Jun Chen

We study the vector Gaussian Chief Executive Officer (CEO) problem under logarithmic loss distortion measure. Specifically, $K \geq 2$ agents observe independently corrupted Gaussian noisy versions of a remote vector Gaussian source, and…

Information Theory · Computer Science 2020-02-05 Yigit Ugur , Inaki Estella Aguerri , Abdellatif Zaidi

In this paper, we are interested in the performance of a variable-length stop-feedback (VLSF) code with $m$ optimal decoding times for the binary-input additive white Gaussian noise channel. We first develop tight approximations on the tail…

Information Theory · Computer Science 2022-02-08 Hengjie Yang , Recep Can Yavas , Victoria Kostina , Richard D. Wesel

In this monograph, we review recent advances in second-order asymptotics for lossy source coding, which provides approximations to the finite blocklength performance of optimal codes. The monograph is divided into three parts. In part I, we…

Information Theory · Computer Science 2024-10-25 Lin Zhou , Mehul Motani

In this paper, we consider the rate-distortion-perception (RDP) trade-off for the lossy compression of a Bernoulli vector source, which is a finite collection of independent binary random variables. The RDP function quantifies in a way the…

Information Theory · Computer Science 2025-01-22 Praneeth Kumar Vippathalla , Mihai-Alin Badiu , Justin P. Coon

We propose to send a Gaussian source over an average-power limited additive white Gaussian noise channel by transmitting a linear combination of the source sequence and the result of its quantization using a high dimensional Gaussian vector…

Information Theory · Computer Science 2007-07-16 Shraga Bross , Amos Lapidoth , Stephan Tinguely

New bounds on the rate distortion function of certain non-Gaussian sources, with a proportional-weighted mean-square error (MSE) distortion measure, are given. The growth, g, of the rate distortion function, as a result of changing from a…

Information Theory · Computer Science 2007-07-13 Jacob Binia

We propose a new method to enforce priors on the solution of the nonnegative matrix factorization (NMF). The proposed algorithm can be used for denoising or single-channel source separation (SCSS) applications. The NMF solution is guided to…

Machine Learning · Computer Science 2013-03-01 Emad M. Grais , Hakan Erdogan

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…

Information Theory · Computer Science 2023-04-25 Yutaka Jitsumatsu

We introduce fundamental bounds on achievable cumulative rate distribution functions (CRDF) to characterize a sequential encoding process that ensures lossless or lossy reconstruction subject to an average distortion criterion using a…

Information Theory · Computer Science 2021-08-31 Hamid Ghourchian , Photios A. Stavrou , 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 zero-delay single-user and multi-user source coding with average distortion constraint and decoder side information. The zero-delay constraint translates into causal (sequential) encoder and decoder pairs as well as the use of…

Information Theory · Computer Science 2013-01-03 Yonatan Kaspi , Neri Merhav

We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are structured linear combinations of columns of this matrix. The…

Information Theory · Computer Science 2014-05-20 Ramji Venkataramanan , Tuhin Sarkar , Sekhar Tatikonda