Results 1 to 10 of about 9,451,730 (348)
Secure Physical Layer Network Coding versus Secure Network Coding [PDF]
When a network has relay nodes, there is a risk that a part of the information is leaked to an untrusted relay. Secure network coding (secure NC) is known as a method to resolve this problem, which enables the secrecy of the message when the message is ...
Masahito Hayashi
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Multiple Linear-Combination Security Network Coding [PDF]
In this paper, we put forward the model of multiple linear-combination security multicast network coding, where the wiretapper desires to obtain some information about a predefined set of multiple linear combinations of the source symbols by ...
Yang Bai, Xuan Guang, Raymond W. Yeung
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Network Coding for Wireless Networks
Reference EPFL-ARTICLE-171957doi:10.1155/2010/359475View record in Web of Science Record created on 2011-12-16, modified on 2016-08 ...
Christina Fragouli +3 more
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A Perpetual Code for Network Coding [PDF]
Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. The drawbacks associated with it are the complexity of the decoding and the overhead resulting from the coding vector. This adds to the overall energy consumption and is problematic for computational limited and battery driven platforms. In this work we present an
Heide, Janus +3 more
semanticscholar +5 more sources
Inspired by holographic codes and tensor-network decoders, we introduce tensor-network stabilizer codes which come with a natural tensor-network decoder. These codes can correspond to any geometry, but, as a special case, we generalize holographic codes beyond those constructed from perfect or block-perfect isometries, and we give an example that ...
Nathan A. McMahon +4 more
openaire +4 more sources
In less than ten years Network Coding has grown from a simple cute idea to an almost revolutionary research trend that has galvanized both the Information-theoretic Community (where it was born) and the Networking Community (where it is expected to find its applications).
Ephremides, A +4 more
openaire +5 more sources
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training [PDF]
Graph representation learning has emerged as a powerful technique for addressing real-world problems. Various downstream graph learning tasks have benefited from its recent developments, such as node classification, similarity search, and graph ...
J. Qiu +7 more
semanticscholar +1 more source
A programmable diffractive deep neural network based on a digital-coding metasurface array
The development of artificial intelligence is typically focused on computer algorithms and integrated circuits. Recently, all-optical diffractive deep neural networks have been created that are based on passive structures and can perform complicated ...
Che Liu +10 more
semanticscholar +1 more source
Network coding has been successfully applied in large-scale content dissemination systems. While network codes provide optimal throughput, its current forms suer from a high decoding complexity. This is an issue when applied to systems composed of nodes with low processing capabilities, such as sensor networks. In this paper, we propose a novel network
Champel, Mary-Luc +3 more
openaire +4 more sources
In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point ...
Liu, Litian +3 more
openaire +6 more sources

