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We propose a simple yet effective wireless network coding and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block…

Information Theory · Computer Science 2016-11-17 Tugcan Aktas , Ali Ozgur Yilmaz , Emre Aktas

We introduce a universal quantization scheme based on random coding, and we analyze its performance. This scheme consists of a source-independent random codebook (typically_mismatched_ to the source distribution), followed by optimal…

Information Theory · Computer Science 2007-07-13 Ioannis Kontoyiannis , Rami Zamir

We consider the problem of distilling uniform random bits from an unknown source with a given $p$-entropy using linear hashing. As our main result, we estimate the expected $p$-divergence from the uniform distribution over the ensemble of…

Information Theory · Computer Science 2025-06-06 Madhura Pathegama , Alexander Barg

The problem of compression in standard information theory consists of assigning codes as short as possible to numbers. Here we consider the problem of optimal coding -- under an arbitrary coding scheme -- and show that it predicts Zipf's…

Computation and Language · Computer Science 2020-09-24 Ramon Ferrer-i-Cancho , Christian Bentz , Caio Seguin

Coding schemes for several problems in network information theory are constructed starting from point-to-point channel codes that are designed for symmetric channels. Given that the point-to-point codes satisfy certain properties pertaining…

Information Theory · Computer Science 2023-10-23 Nadim Ghaddar , Shouvik Ganguly , Lele Wang , Young-Han Kim

We derive various error exponents in the bee identification problem under two different decoding rules. Under na\"ive decoding, which decodes each bee independently of the others, we analyze a general discrete memoryless channel and a…

Information Theory · Computer Science 2020-11-20 Ran Tamir , Neri Merhav

Second order asymptotics of fixed-length source coding and intrinsic randomness is discussed with a constant error constraint. There was a difference between optimal rates of fixed-length source coding and intrinsic randomness, which never…

Information Theory · Computer Science 2010-01-23 Masahito Hayashi

We address the problem of bounding below the probability of error under maximum likelihood decoding of a binary code with a known distance distribution used on a binary symmetric channel. An improved upper bound is given for the maximum…

Information Theory · Computer Science 2007-07-16 Alexander Barg , Andrew McGregor

Interactive encoding and decoding based on binary low-density parity-check codes with syndrome accumulation (SA-LDPC-IED) is proposed and investigated. Assume that the source alphabet is $\mathbf{GF}(2)$, and the side information alphabet…

Information Theory · Computer Science 2015-03-20 Jin Meng , En-Hui Yang

In this paper, we consider the one-shot version of the classical Wyner-Ziv problem where a source is compressed in a lossy fashion when only the decoder has access to a correlated side information. Following the entropy-constrained…

Information Theory · Computer Science 2024-05-06 Oğuzhan Kubilay Ülger , Elza Erkip

A statistical estimation algorithm of the weight distribution of a linear code is shown, based on using its generator matrix as a compression function on random bit strings.

Information Theory · Computer Science 2018-06-07 Alessandro Tomasi , Alessio Meneghetti

Constrained coding is used widely in digital communication and storage systems. In this paper, we study a generalized sliding window constraint called the skip-sliding window. A skip-sliding window (SSW) code is defined in terms of the…

Information Theory · Computer Science 2018-01-12 Ting-Yi Wu , Anshoo Tandon , Lav R. Varshney , Mehul Motani

When randomized ensembles such as bagging or random forests are used for binary classification, the prediction error of the ensemble tends to decrease and stabilize as the number of classifiers increases. However, the precise relationship…

Probability · Mathematics 2019-05-01 Miles E. Lopes

The likelihood decoder is a stochastic decoder that selects the decoded message at random, using the posterior distribution of the true underlying message given the channel output. In this work, we study a generalized version of this…

Information Theory · Computer Science 2016-11-17 Neri Merhav

Like image coding in visual data transmission, feature coding is essential for the distributed deployment of large models by significantly reducing transmission and storage burden. However, prior studies have mostly targeted task- or…

Multimedia · Computer Science 2025-09-03 Changsheng Gao , Zijie Liu , Li Li , Dong Liu , Xiaoyan Sun , Weisi Lin

We study how finite-window sampling (random spatial truncation) and reciprocal-space radial binning influence the detection of hyperuniformity in disordered systems. Using thirteen representative two-dimensional simulation systems (two…

Disordered Systems and Neural Networks · Physics 2026-03-10 Yuan Liu , Xurui Li , Jianxiang Tian , Xunwang Yan , Ge Zhang

Iterative bit flipping decoders are an efficient and effective decoder choice for decoding codes which admit a sparse parity-check matrix. Among these, sparse $(v,w)$-regular codes, which include LDPC and MDPC codes are of particular…

Cryptography and Security · Computer Science 2025-01-24 Alessandro Annechini , Alessandro Barenghi , Gerardo Pelosi

This paper considers a general framework for massive random access based on sparse superposition coding. We provide guidelines for the code design and propose the use of constant-weight codes in combination with a dictionary design based on…

Information Theory · Computer Science 2022-07-27 Patrick Agostini , Zoran Utkovski , Alexis Decurninge , Maxime Guillaud , Slawomir Stanczak

In a lossless compression system with target lengths, a compressor ${\cal C}$ maps an integer $m$ and a binary string $x$ to an $m$-bit code $p$, and if $m$ is sufficiently large, a decompressor ${\cal D}$ reconstructs $x$ from $p$. We call…

Information Theory · Computer Science 2019-11-12 Bruno Bauwens , Marius Zimand

We consider the problem of source compression under three different scenarios in the one-shot (non- asymptotic) regime. To be specific, we prove one-shot achievability and converse bounds on the coding rates for distributed source coding,…

Information Theory · Computer Science 2015-12-11 Naqueeb Ahmad Warsi