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The strongly correlated systems we use to realise quantum error-correcting codes may give rise to high-weight, problematic errors. Encouragingly, we can expect local quantum error-correcting codes with no string-like logical operators $-$…

Quantum Physics · Physics 2021-07-14 Georgia M. Nixon , Benjamin J. Brown

In a {\em locally recoverable} or {\em repairable} code, any symbol of a codeword can be recovered by reading only a small (constant) number of other symbols. The notion of local recoverability is important in the area of distributed…

Information Theory · Computer Science 2016-11-17 Viveck Cadambe , Arya Mazumdar

In this paper, we prove that with high probability, random Reed-Solomon codes approach the half-Singleton bound - the optimal rate versus error tradeoff for linear insdel codes - with linear-sized alphabets. More precisely, we prove that,…

Information Theory · Computer Science 2024-07-11 Roni Con , Zeyu Guo , Ray Li , Zihan Zhang

Gallager-type error-correcting codes that nearly saturate Shannon's bound are constructed using insight gained from mapping the problem onto that of an Ising spin system. The performance of the suggested codes is evaluated for different…

Disordered Systems and Neural Networks · Physics 2009-10-31 Ido Kanter , David Saad

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

The problem of coding for networks experiencing worst-case symbol errors is considered. We argue that this is a reasonable model for highly dynamic wireless network transmissions. We demonstrate that in this setup prior network…

Information Theory · Computer Science 2015-10-13 Qiwen Wang , Sidharth Jaggi

We define a notion of network capacity region of networks that generalizes the notion of network capacity defined by Cannons et al. and prove its notable properties such as closedness, boundedness and convexity when the finite field is…

Information Theory · Computer Science 2016-11-17 Anthony Kim , Muriel Medard

This paper presents an efficient algorithm for robust network reconstruction of Linear Time-Invariant (LTI) systems in the presence of noise, estimation errors and unmodelled nonlinearities. The method here builds on previous work on robust…

Dynamical Systems · Mathematics 2016-11-18 David Hayden , Ye Yuan , Jorge Gonçalves

The cover metric is suitable for describing the resilience against correlated errors in arrays, in particular crisscross errors, which makes it interesting for applications such as distributed data storage (DDS). In this work, we consider…

Information Theory · Computer Science 2018-09-05 Hedongliang Liu , Lukas Holzbaur , Antonia Wachter-Zeh

A locally repairable code is called Singleton-optimal if it achieves the Singleton-type bound. Such codes are of great theoretic interest in the study of locally repairable codes. In the recent years there has been a great amount of work on…

Information Theory · Computer Science 2022-07-13 Shu Liu , Tingyi Wu , Chaoping Xing , Chen Yuan

In this paper q-ary Raptor codes under ML decoding are considered. An upper bound on the probability of decoding failure is derived using the weight enumerator of the outer code, or its expected weight enumerator if the outer code is drawn…

Information Theory · Computer Science 2016-11-21 Francisco Lázaro , Gianluigi Liva , Enrico Paolini , Gerhard Bauch

In this paper, we propose a methodology to compute the optimal finite-length coding rate for random linear network coding schemes over a line network. To do so, we first model the encoding, reencoding, and decoding process of different…

Networking and Internet Architecture · Computer Science 2018-05-16 Tan Do-Duy , M. Ángeles Vázquez-Castro

In this work, we study linear error-correcting codes against adversarial insertion-deletion (indel) errors. While most constructions for the indel model are nonlinear, linear codes offer compact representations, efficient encoding, and…

Information Theory · Computer Science 2025-10-01 Roee Gross , Roni Con , Eitan Yaakobi

We investigate the relation between the girth and the guaranteed error correction capability of $\gamma$-left regular LDPC codes when decoded using the bit flipping (serial and parallel) algorithms. A lower bound on the number of variable…

Information Theory · Computer Science 2016-11-17 Shashi Kiran Chilappagari , Dung Viet Nguyen , Bane Vasic , Michael Marcellin

An upper bound on the error probability of specific lattices, based on their distance-spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers.…

Information Theory · Computer Science 2013-01-03 Yuval Domb , Meir Feder

Network reconstruction consists in determining the unobserved pairwise couplings between $N$ nodes given only observational data on the resulting behavior that is conditioned on those couplings -- typically a time-series or independent…

Data Structures and Algorithms · Computer Science 2024-05-08 Tiago P. Peixoto

The problem of error-control in random linear network coding is considered. A ``noncoherent'' or ``channel oblivious'' model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer…

Information Theory · Computer Science 2008-03-25 Ralf Koetter , Frank Kschischang

A Viterbi-like decoding algorithm is proposed in this paper for generalized convolutional network error correction coding. Different from classical Viterbi algorithm, our decoding algorithm is based on minimum error weight rather than the…

Information Theory · Computer Science 2019-02-12 Hengjie Yang , Wangmei Guo

An Artificial Neural Network-based error compensation method is proposed for improving the accuracy of resolver-based 16-bit encoders by compensating for their respective systematic error profiles. The error compensation procedure, for a…

Neural and Evolutionary Computing · Computer Science 2015-05-14 V. K. Dhar , A. K. Tickoo , S. K. Kaul , R. Koul , B. P. Dubey

Neural networks can efficiently encode the probability distribution of errors in an error correcting code. Moreover, these distributions can be conditioned on the syndromes of the corresponding errors. This paves a path forward for a…

Quantum Physics · Physics 2017-09-12 Stefan Krastanov , Liang Jiang