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Lossy image coding is the art of computing that is principally bounded by the image's rate-distortion function. This bound, though never accurately characterized, has been approached practically via deep learning technologies in recent…

Information Theory · Computer Science 2025-01-22 Haotian Zhang , Dong Liu

In general coding theory, we often assume that error is observed in transferring or storing encoded symbols, while the process of encoding itself is error-free. Motivated by recent applications of coding theory, in this paper, we consider…

Information Theory · Computer Science 2021-03-02 Nastaran Abadi Khooshemehr , Mohammad Ali Maddah-Ali

We consider the problem of block-coded communication, where in each block, the channel law belongs to one of two disjoint sets. The decoder is aimed to decode only messages that have undergone a channel from one of the sets, and thus has to…

Information Theory · Computer Science 2015-09-08 Nir Weinberger , Neri Merhav

We continue the study of rateless codes for transmission of information across channels whose rate of erasure is unknown. In such a code, an infinite stream of encoding symbols can be generated from the message and sent across the erasure…

Information Theory · Computer Science 2021-01-28 Shashwat Silas

We consider transmission of a continuous amplitude source over an L-block Rayleigh fading $M_t \times M_r$ MIMO channel when the channel state information is only available at the receiver. Since the channel is not ergodic, Shannon's…

Information Theory · Computer Science 2007-11-09 Deniz Gunduz , Elza Erkip

We present a novel distributed computing framework that is robust to slow compute nodes, and is capable of both approximate and exact computation of linear operations. The proposed mechanism integrates the concepts of randomized sketching…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-06 Burak Bartan , Mert Pilanci

We present and analyze a joint source-channel coding strategy for the transmission of a Gaussian source across a Gaussian channel in n channel uses per source symbol. Among all such strategies, our scheme has the following properties: i)…

Information Theory · Computer Science 2016-11-18 Marius Kleiner , Bixio Rimoldi

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…

Information Theory · Computer Science 2020-12-02 Maxim Goukhshtein , Petros T. Boufounos , Toshiaki Koike-Akino , Stark C. Draper

We examine the issue of separation and code design for networks that operate over finite fields. We demonstrate that source-channel (or source-network) separation holds for several canonical network examples like the noisy multiple access…

Information Theory · Computer Science 2007-07-13 Siddharth Ray , Michelle Effros , Muriel Medard , Ralf Koetter , Tracey Ho , David Karger , Jinane Abounadi

Our primary goal in this paper is to traverse the performance gap between two linear network coding schemes: random linear network coding (RLNC) and instantly decodable network coding (IDNC) in terms of throughput and decoding delay. We…

Information Theory · Computer Science 2013-09-06 Mingchao Yu , Neda Aboutorab , Parastoo Sadeghi

In this paper, channel optimized distributed multiple description vector quantization (CDMD) schemes are presented for distributed source coding in symmetric and asymmetric settings. The CDMD encoder is designed using a deterministic…

Information Theory · Computer Science 2015-05-20 Mehrdad Valipour , Farshad Lahouti

In this paper, we study the three-node Decode-and-Forward (D&F) relay network subject to random and burst packet erasures. The source wishes to transmit an infinite stream of packets to the destination via the relay. The three-node D&F…

Information Theory · Computer Science 2022-11-30 Shubhransh Singhvi , Gayathri R. , P. Vijay Kumar

Nowadays polar codes are becoming one of the most favorable capacity achieving error correction codes for their low encoding and decoding complexity. However, due to the large code length required by practical applications, the few existing…

Hardware Architecture · Computer Science 2011-11-04 Chuan Zhang , Bo Yuan , Keshab K. Parhi

The design and implementation of error correcting codes has long been informed by two fundamental results: Shannon's 1948 capacity theorem, which established that long codes use noisy channels most efficiently; and Berlekamp, McEliece, and…

Information Theory · Computer Science 2024-10-30 Ken R. Duffy , Muriel Médard , Wei An

We present a new lossy compressor for discrete sources. For coding a source sequence $x^n$, the encoder starts by assigning a certain cost to each reconstruction sequence. It then finds the reconstruction that minimizes this cost and…

Information Theory · Computer Science 2009-01-19 Shirin Jalali , Andrea Montanari , Tsachy Weissman

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…

Information Theory · Computer Science 2020-10-21 Farhad Shirani , S. Sandeep Pradhan

Polyanskiy proposed a framework for the unsourced multiple access channel (MAC) problem where users employ a common codebook in the finite blocklength regime. However, existing approaches handle channel noise before the joint decoder. In…

Information Theory · Computer Science 2026-04-14 Yuming Han , Yuxin Long

An analog source is to be transmitted across a Gaussian channel in more than one channel use per source symbol. This paper derives a lower bound on the asymptotic mean squared error for a strategy that consists of repeatedly quantizing the…

Information Theory · Computer Science 2016-11-17 Marius Kleiner , Bixio Rimoldi

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the…

Information Theory · Computer Science 2013-03-01 Venkatesan Guruswami , Adam Smith

The deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability d, and when they are not deleted, they are not affected by the channel.…

Information Theory · Computer Science 2011-05-02 Yashodhan Kanoria , Andrea Montanari
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