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相关论文: Dispersion of Gaussian Sources with Memory and an …

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The Gauss-Markov source produces $U_i = aU_{i-1} + Z_i$ for $i\geq 1$, where $U_0 = 0$, $|a|<1$ and $Z_i\sim\mathcal{N}(0, \sigma^2)$ are i.i.d. Gaussian random variables. We consider lossy compression of a block of $n$ samples of the…

信息论 · 计算机科学 2019-09-26 Peida Tian , Victoria Kostina

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…

信息论 · 计算机科学 2016-11-15 Victoria Kostina , Sergio Verdú

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…

信息论 · 计算机科学 2011-02-15 Amir Ingber , Yuval Kochman

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

信息论 · 计算机科学 2017-02-28 Victoria Kostina

We study the moderate-deviations (MD) setting for lossy source coding of stationary memoryless sources. More specifically, we derive fundamental compression limits of source codes whose rates are $R(D) \pm \epsilon_n$, where $R(D)$ is the…

信息论 · 计算机科学 2012-05-11 Vincent Y. F. Tan

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…

信息论 · 计算机科学 2016-01-26 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar , Tsachy Weissman

Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

信息论 · 计算机科学 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

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…

信息论 · 计算机科学 2017-01-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

We study the problem of communicating a distributed correlated memoryless source over a memoryless network, from source nodes to destination nodes, under quadratic distortion constraints. We establish the following two complementary…

信息论 · 计算机科学 2013-04-09 Himanshu Asnani , Ilan Shomorony , A. Salman Avestimehr , Tsachy Weissman

Consider a Gaussian memoryless multiple source with $m$ components with joint probability distribution known only to lie in a given class of distributions. A subset of $k \leq m$ components are sampled and compressed with the objective of…

信息论 · 计算机科学 2018-03-16 Vinay Praneeth Boda

This paper studies the fundamental limits of the minimum average length of lossless and lossy variable-length compression, allowing a nonzero error probability $\epsilon$, for lossless compression. We give non-asymptotic bounds on the…

信息论 · 计算机科学 2015-10-09 Victoria Kostina , Yury Polyanskiy , Sergio Verdú

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…

信息论 · 计算机科学 2007-07-13 Jacob Binia

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…

信息论 · 计算机科学 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

We begin by presenting a simple lossy compressor operating at near-zero rate: The encoder merely describes the indices of the few maximal source components, while the decoder's reconstruction is a natural estimate of the source components…

信息论 · 计算机科学 2016-03-09 Albert No , Tsachy Weissman

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…

信息论 · 计算机科学 2022-06-06 Siyao Zhou , Sadaf Salehkalaibar , Jingjing Qian , Jun Chen , Wuxian Shi , Yiqun Ge , Wen Tong

The problem of lossless data compression with side information available to both the encoder and the decoder is considered. The finite-blocklength fundamental limits of the best achievable performance are defined, in two different versions…

信息论 · 计算机科学 2021-02-23 Lampros Gavalakis , Ioannis Kontoyiannis

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the…

信息论 · 计算机科学 2014-10-13 Sy-Quoc Le , Vincent Y. F. Tan , Mehul Motani

We examine the coordinated and universal rate-efficient sampling of a subset of correlated discrete memoryless sources followed by lossy compression of the sampled sources. The goal is to reconstruct a predesignated subset of sources within…

信息论 · 计算机科学 2017-06-23 Vinay Praneeth Boda , Prakash Narayan

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is…

信息论 · 计算机科学 2016-09-19 Victoria Kostina , Sergio Verdú

We consider the transmission of a memoryless bivariate Gaussian source over an average-power-constrained one-to-two Gaussian broadcast channel. The transmitter observes the source and describes it to the two receivers by means of an…

信息论 · 计算机科学 2009-03-20 Shraga Bross , Amos Lapidoth , Stephan Tinguely
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