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We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problems. As a corollary, this inequality yields a generalization of the…

Information Theory · Computer Science 2007-07-13 Tie Liu , Pramod Viswanath

We establish sharp tail asymptotics for component-wise extreme values of bivariate Gaussian random vectors with arbitrary correlation between the components. We consider two scaling regimes for the tail event in which we demonstrate the…

Probability · Mathematics 2019-03-28 Remco van der Hofstad , Harsha Honnappa

The extremal inequality approach plays a key role in network information theory problems. In this paper, we propose a novel monotone path construction in product probability space. The optimality of Gaussian distribution is then established…

Information Theory · Computer Science 2021-09-02 Yinfei Xu , Guojun Chen

In this work, the rate region of the vector Gaussian multiple description problem with individual and central quadratic distortion constraints is studied. In particular, an outer bound to the rate region of the L-description problem is…

Information Theory · Computer Science 2016-11-18 Guoqiang Zhang , W. Bastiaan Kleijn , Jan Østergaard

We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain. The constants in this inequality are explicit and depend on computable bounds on the mixing rate of the…

Statistics Theory · Mathematics 2013-03-05 Gersende Fort , Eric Moulines , Pierre Priouret , Pierre Vandekerkhove

We investigate the problem of the successive refinement for Wyner-Ziv coding with degraded side information and obtain a complete characterization of the rate region for the quadratic vector Gaussian case. The achievability part is based on…

Information Theory · Computer Science 2020-02-19 Yinfei Xu , Xuan Guang , Jian Lu , Jun Chen

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 derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process when the channel is a discrete memoryless, while a previous study solved it only in a special case. We also…

Information Theory · Computer Science 2024-09-10 Ryo Yaguchi , Masahito Hayashi

We consider the problem of source coding subject to a fidelity criterion for the Gray-Wyner network that connects a single source with two receivers via a common channel and two private channels. The pareto-optimal trade-offs between the…

Information Theory · Computer Science 2020-10-01 Erixhen Sula , Michael Gastpar

L multiple descriptions of a vector Gaussian source for individual and central receivers are investigated. The sum rate of the descriptions with covariance distortion measure constraints, in a positive semidefinite ordering, is exactly…

Information Theory · Computer Science 2007-07-13 H. Wang , P. Viswanath

Markov networks are frequently used in sciences to represent conditional independence relationships underlying observed variables arising from a complex system. It is often of interest to understand how an underlying network differs between…

Methodology · Statistics 2021-04-26 Byol Kim , Song Liu , Mladen Kolar

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 determine the rate region of the quadratic Gaussian two-encoder source-coding problem. This rate region is achieved by a simple architecture that separates the analog and digital aspects of the compression. Furthermore, this architecture…

Information Theory · Computer Science 2008-02-09 Aaron B. Wagner , Saurabha Tavildar , Pramod Viswanath

Consider the two-way rate-distortion problem in which a helper sends a common limited-rate message to both users based on side information at its disposal. We characterize the region of achievable rates and distortions where a Markov form…

Information Theory · Computer Science 2009-04-06 Haim Permuter , Yossi Steinberg , Tsachy Weissman

We establish the rate region of an extended Gray-Wyner system for 2-DMS $(X,Y)$ with two additional decoders having complementary causal side information. This extension is interesting because in addition to the operationally significant…

Information Theory · Computer Science 2018-12-11 Cheuk Ting Li , Abbas El Gamal

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

Maximum likelihood estimation of large Markov-switching vector autoregressions (MS-VARs) can be challenging or infeasible due to parameter proliferation. To accommodate situations where dimensionality may be of comparable order to or…

Econometrics · Economics 2021-07-28 Kenwin Maung

We propose two new measures for extracting the unique information in $X$ and not $Y$ about a message $M$, when $X, Y$ and $M$ are joint random variables with a given joint distribution. We take a Markov based approach, motivated by…

Information Theory · Computer Science 2023-07-21 Keerthana Gurushankar , Praveen Venkatesh , Pulkit Grover

We determine the rate region of the vector Gaussian one-helper source-coding problem under a covariance matrix distortion constraint. The rate region is achieved by a simple scheme that separates the lossy vector quantization from the…

Information Theory · Computer Science 2011-12-30 Md. Saifur Rahman , Aaron B. Wagner

This paper quantifies the intuitive observation that adding noise reduces available information by means of non-linear strong data processing inequalities. Consider the random variables $W\to X\to Y$ forming a Markov chain, where $Y=X+Z$…

Information Theory · Computer Science 2017-11-21 Flavio P. Calmon , Yury Polyanskiy , Yihong Wu
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