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We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortion is uncorrelated to the input. The solution is given by two…

Information Theory · Computer Science 2008-01-14 Milan S. Derpich , Jan Ostergaard , Graham C. Goodwin

This paper is concerned with a rate-distortion theory for sequences of i.i.d. random variables with general distribution supported on general sets including manifolds and fractal sets. Manifold structures are prevalent in data science,…

Information Theory · Computer Science 2018-04-25 Erwin Riegler , Günther Koliander , Helmut Bölcskei

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

We study estimation of an $s$-sparse signal in the $p$-dimensional Gaussian sequence model with equicorrelated observations and derive the minimax rate. A new phenomenon emerges from correlation, namely the rate scales with respect to…

Statistics Theory · Mathematics 2025-01-23 Subhodh Kotekal , Chao Gao

For $p \in (0,1)$, sample a binary sequence from the infinite product measure of Bernoulli$(p)$ distributions. It is known that for $p=1/2$, almost every binary sequence is Poisson generic in the sense of Peres and Weiss, a property that…

Probability · Mathematics 2025-09-30 Jon V. Kogan , Nicolò Paviato

This paper investigates the rate-distortion function, under a squared error distortion $D$, for an $n$-dimensional random vector uniformly distributed on an $(n-1)$-sphere of radius $R$. First, an expression for the rate-distortion function…

Information Theory · Computer Science 2024-01-10 Alex Dytso , Martina Cardone

The problem of compressing a real-valued sparse source using compressive sensing techniques is studied. The rate distortion optimality of a coding scheme in which compressively sensed signals are quantized and then reconstructed is…

Information Theory · Computer Science 2010-11-09 Rajiv Soundararajan , Sriram Vishwanath

Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as neural image compression. When compressed data is transmitted over public communication…

Information Theory · Computer Science 2026-04-23 Gustaf Åhlgren , Onur Günlü

As shown by M\'edard, the capacity of fading channels with imperfect channel-state information (CSI) can be lower-bounded by assuming a Gaussian channel input $X$ with power $P$ and by upper-bounding the conditional entropy $h(X|Y,\hat{H})$…

Information Theory · Computer Science 2016-11-15 Adriano Pastore , Tobias Koch , Javier Rodríguez Fonollosa

Using combinatorial arguments, we determine an upper bound on achievable rates of stabilizer codes used over the quantum erasure channel. This allows us to recover the no-cloning bound on the capacity of the quantum erasure channel, R is…

Quantum Physics · Physics 2016-11-29 Nicolas Delfosse , Gilles Zémor

We study the statistical limits of both detecting and estimating a rank-one deformation of a symmetric random Gaussian tensor. We establish upper and lower bounds on the critical signal-to-noise ratio, under a variety of priors for the…

Probability · Mathematics 2017-01-25 Amelia Perry , Alexander S. Wein , Afonso S. Bandeira

We propose a new construction for low-density source codes with multiple parameters that can be tuned to optimize the performance of the code. In addition, we introduce a set of analysis techniques for deriving upper bounds for the expected…

Information Theory · Computer Science 2007-07-13 Emin Martinian , Martin J. Wainwright

We extend the Rate-Distortion-Perception (RDP) framework to the R\'enyi information-theoretic regime, utilizing Sibson's $\alpha$-mutual information to characterize the fundamental limits under distortion and perception constraints. For…

Information Theory · Computer Science 2026-05-12 Jiahui Wei , Marios Kountouris

In this paper, we provide three applications for $f$-divergences: (i) we introduce Sanov's upper bound on the tail probability of the sum of independent random variables based on super-modular $f$-divergence and show that our generalized…

Information Theory · Computer Science 2023-01-27 Saeed Masiha , Amin Gohari , Mohammad Hossein Yassaee

For the HB problem with the CR constraint, the rate-distortion function is derived under the assumption that the side information sequences are (stochastically) degraded. The rate-distortion function is also calculated explicitly for three…

Information Theory · Computer Science 2016-11-18 Behzad Ahmadi , Ravi Tandon , Osvaldo Simeone , H. Vincent Poor

We consider a problem of coding for computing, where the decoder wishes to estimate a function of its local message and the source message at the encoder within a given distortion. We show that the rate-distortion function can be…

Information Theory · Computer Science 2022-05-18 Deheng Yuan , Tao Guo , Bo Bai , Wei Han

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

A new source model, which consists of an intrinsic state part and an extrinsic observation part, is proposed and its information-theoretic characterization, namely its rate-distortion function, is defined and analyzed. Such a source model…

Information Theory · Computer Science 2022-06-02 Jiakun Liu , Shuo Shao , Wenyi Zhang , H. Vincent Poor

In this paper we derive information theoretic performance bounds to sensing and reconstruction of sparse phenomena from noisy projections. We consider two settings: output noise models where the noise enters after the projection and input…

Information Theory · Computer Science 2011-12-22 Shuchin Aeron , Venkatesh Saligrama , Manqi Zhao

Standard sparse pseudo-input approximations to the Gaussian process (GP) cannot handle complex functions well. Sparse spectrum alternatives attempt to answer this but are known to over-fit. We suggest the use of variational inference for…

Machine Learning · Statistics 2015-03-23 Yarin Gal , Richard Turner