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Related papers: Quasi-linear Network Coding

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Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. Some of its practical drawbacks are the complexity of decoding and the overhead due to the coding vectors. For computationally weak and battery-driven…

Networking and Internet Architecture · Computer Science 2015-09-16 Janus Heide , Morten V. Pedersen , Frank H. P. Fitzek , Muriel M edard

Real-time applications require latencies on the order of a millisecond with very high reliabilities, paralleling the requirements for high-performance industrial control. Current wireless technologies like WiFi, Bluetooth, LTE, etc. are…

Information Theory · Computer Science 2018-03-15 Vasuki Narasimha Swamy , Paul Rigge , Gireeja Ranade , Anant Sahai , Borivoje Nikolic

A combinatorial framework for adversarial network coding is presented. Channels are described by specifying the possible actions that one or more (possibly coordinated) adversaries may take. Upper bounds on three notions of capacity (the…

Information Theory · Computer Science 2017-06-20 Alberto Ravagnani , Frank R. Kschischang

Linear quasi-cyclic product codes over finite fields are investigated. Given the generating set in the form of a reduced Gr{\"o}bner basis of a quasi-cyclic component code and the generator polynomial of a second cyclic component code, an…

Information Theory · Computer Science 2015-01-27 Alexander Zeh , San Ling

Random linear network coding is a particularly decentralized approach to the multicast problem. Use of random network codes introduces a non-zero probability however that some sinks will not be able to successfully decode the required…

Information Theory · Computer Science 2007-07-13 Adria Tauste-Campo , Alex Grant

Quasi-cyclic codes form an important class of algebraic codes that includes cyclic codes as a special subclass. This chapter focuses on the algebraic structure of quasi-cyclic codes, first. Based on these structural properties, some…

Information Theory · Computer Science 2020-12-10 Cem Güneri , San Ling , Buket Özkaya

A new network construction method is presented for building of scalable, high throughput, low latency networks. The method is based on the exact equivalence discovered between the problem of maximizing network throughput (measured as…

Information Theory · Computer Science 2013-02-06 Ratko V. Tomic

Linear network coding transmits data through networks by letting the intermediate nodes combine the messages they receive and forward the combinations towards their destinations. The solvability problem asks whether the demands of all the…

Information Theory · Computer Science 2014-12-18 Maximilien Gadouleau , Adrien Richard , Eric Fanchon

Artificial neural networks have gone through a recent rise in popularity, achieving state-of-the-art results in various fields, including image classification, speech recognition, and automated control. Both the performance and…

Neural and Evolutionary Computing · Computer Science 2016-11-08 Sean C. Smithson , Guang Yang , Warren J. Gross , Brett H. Meyer

This paper proposes Fulcrum network codes, a network coding framework that achieves three seemingly conflicting objectives: (i) to reduce the coding coefficient overhead to almost n bits per packet in a generation of n packets; (ii) to…

Information Theory · Computer Science 2015-11-19 Daniel E. Lucani , Morten V. Pedersen , Diego Ruano , Chres W. Sørensen , Frank H. P. Fitzek , Janus Heide , Olav Geil

While feasibility and obtaining a solution of a given network coding problem are well studied, the decoding procedure and complexity have not garnered much attention. We consider the decoding problem in a network wherein the sources…

Information Theory · Computer Science 2015-10-14 Anindya Gupta , B. Sundar Rajan

Neural networks are famously nonlinear. However, linearity is defined relative to a pair of vector spaces, $f:X \to Y$. Leveraging the algebraic concept of transport of structure, we propose a method to explicitly identify non-standard…

Machine Learning · Computer Science 2026-02-23 Nimrod Berman , Assaf Hallak , Assaf Shocher

Although deep neural networks are highly effective, their high computational and memory costs severely challenge their applications on portable devices. As a consequence, low-bit quantization, which converts a full-precision neural network…

Computer Vision and Pattern Recognition · Computer Science 2019-12-02 Jiwei Yang , Xu Shen , Jun Xing , Xinmei Tian , Houqiang Li , Bing Deng , Jianqiang Huang , Xiansheng Hua

In recent years, network coding has been investigated as a method to obtain improvements in wireless networks. A typical assumption of previous work is that relay nodes performing network coding can decode the messages from sources…

Information Theory · Computer Science 2007-07-13 Sichao Yang , Ralf Koetter

The relations, rather than the elements, constitute the structure of networks. We therefore develop a systematic approach to the analysis of networks, modelled as graphs or hypergraphs, that is based on structural properties of…

Discrete Mathematics · Computer Science 2020-12-08 Marzieh Eidi , Amirhossein Farzam , Wilmer Leal , Areejit Samal , Jürgen Jost

In topologically-protected quantum computation, quantum gates can be carried out by adiabatically braiding two-dimensional quasiparticles, reminiscent of entangled world lines. Bonesteel et al. [Phys. Rev. Lett. 95, 140503 (2005)], as well…

Quantum Physics · Physics 2013-02-14 Ross B. McDonald , Helmut G. Katzgraber

We consider a lossy multicast network in which the reliability is provided by means of Random Linear Network Coding. Our goal is to characterise the performance of such network in terms of the probability that a source message is delivered…

Information Theory · Computer Science 2018-02-01 Evgeny Tsimbalo , Andrea Tassi , Robert J. Piechocki

This paper investigates the construction of linear network codes for broadcasting a set of data packets to a number of users. The links from the source to the users are modeled as independent erasure channels. Users are allowed to inform…

Information Theory · Computer Science 2013-12-10 Chi Wan Sung , Linyu Huang , Ho Yuet Kwan , Kenneth W. Shum

We consider methods for quantifying the similarity of vertices in networks. We propose a measure of similarity based on the concept that two vertices are similar if their immediate neighbors in the network are themselves similar. This leads…

Physics and Society · Physics 2007-05-23 E. A. Leicht , Petter Holme , M. E. J. Newman

We analyze a new group testing scheme, termed semi-quantitative group testing, which may be viewed as a concatenation of an adder channel and a discrete quantizer. Our focus is on non-uniform quantizers with arbitrary thresholds. For the…

Information Theory · Computer Science 2015-06-26 Amin Emad , Olgica Milenkovic