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相关论文: Lattices for Distributed Source Coding: Jointly Ga…

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A multiple-descriptions (MD) coding strategy is proposed and an inner bound to the achievable rate-distortion region is derived. The scheme utilizes linear codes. It is shown in two different MD set-ups that the linear coding scheme…

信息论 · 计算机科学 2014-02-11 Farhad Shirani , Sandeep Pradhan

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

信息论 · 计算机科学 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

In this work, we investigate an instance of the Heegard-Berger problem with two sources and arbitrarily correlated side information sequences at two decoders, in which the reconstruction sets at the decoders are degraded. Specifically, two…

信息论 · 计算机科学 2015-08-27 Meryem Benammar , Abdellatif Zaidi

We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those…

信息论 · 计算机科学 2007-07-13 Nan Liu , Sennur Ulukus

We study a new encoding scheme for lossy source compression based on spatially coupled low-density generator-matrix codes. We develop a belief-propagation guided-decimation algorithm, and show that this algorithm allows to approach the…

信息论 · 计算机科学 2012-02-23 Vahid Aref , Nicolas Macris , Rudiger Urbanke , Marc Vuffray

We consider the k-encoder source coding problem with a quadratic distortion measure. We show that among all source distributions with a given covariance matrix K, the jointly Gaussian source requires the highest rates in order to meet a…

信息论 · 计算机科学 2016-11-15 Ilan Shomorony , A. Salman Avestimehr , Himanshu Asnani , Tsachy Weissman

This work investigates functional source coding problems with maximal distortion, motivated by approximate function computation in many modern applications. The maximal distortion treats imprecise reconstruction of a function value as good…

信息论 · 计算机科学 2022-12-29 Sourya Basu , Daewon Seo , Lav R. Varshney

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…

信息论 · 计算机科学 2024-10-14 Evagoras Stylianou , Michail Gkagkos , Charalambos D. Charalambous

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

In this paper, we consider a scalar-help-vector source coding problem for $L+1$ correlated Gaussian memoryless sources. We deal with the case where $L$ encoders observe noisy linear combinations of $K$ correlated Gaussian scalar sources…

信息论 · 计算机科学 2019-11-14 C. Deng , S. Wu , Q. Zhang

In this paper, distributed (or multiterminal) source coding with one distortion criterion and correlated messages is considered. This problem can be also called ``Berger-Yeung problem with correlated messages''. It corresponds to the source…

信息论 · 计算机科学 2009-08-18 Suhan Choi

In this paper we propose a new framework for distributed source coding of structured sources, such as sparse signals. Our framework capitalizes on recent advances in the theory of linear inverse problems and signal representations using…

信息论 · 计算机科学 2020-12-02 Maxim Goukhshtein , Petros T. Boufounos , Toshiaki Koike-Akino , Stark C. Draper

We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization…

信息论 · 计算机科学 2008-07-24 Milan S. Derpich , Jan Ostergaard , Daniel E. Quevedo

Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nodes iteratively compute the sample average of the data stored…

信息论 · 计算机科学 2021-12-06 Ryan Pilgrim

Let (S1,i, S2,i), distributed according to i.i.d p(s1, s2), i = 1, 2, . . . be a memoryless, correlated partial side information sequence. In this work we study channel coding and source coding problems where the partial side information…

信息论 · 计算机科学 2013-04-12 Avihay Shirazi , Uria Basher , Haim Permuter

Transmission of a Gaussian source over a time-varying Gaussian channel is studied in the presence of time-varying correlated side information at the receiver. A block fading model is considered for both the channel and the side information,…

信息论 · 计算机科学 2015-05-27 Iñaki Estella Aguerri , Deniz Gündüz

We establish a duality result between linear index coding and Locally Repairable Codes (LRCs). Specifically, we show that a natural extension of LRCs we call Generalized Locally Repairable Codes (GLCRs) are exactly dual to linear index…

信息论 · 计算机科学 2014-02-18 Karthikeyan Shanmugam , Alexandros G. Dimakis

Lattices possess elegant mathematical properties which have been previously used in the literature to show that structured codes can be efficient in a variety of communication scenarios, including coding for the additive white Gaussian…

信息论 · 计算机科学 2017-12-19 Lakshmi Natarajan , Yi Hong , Emanuele Viterbo

We consider the distributed source coding problem in which correlated data picked up by scattered sensors has to be encoded separately and transmitted to a common receiver, subject to a rate-distortion constraint. Although near-tooptimal…

信息论 · 计算机科学 2008-09-09 G. Maierbacher , J. Barros

In this work, lossy distributed compression of pairs of correlated sources is considered. Conventionally, Shannon's random coding arguments -- using randomly generated unstructured codebooks whose blocklength is taken to be asymptotically…

信息论 · 计算机科学 2020-10-21 Farhad Shirani , S. Sandeep Pradhan