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We study the tandem duplication distance between binary sequences and their roots. In other words, the quantity of interest is the number of tandem duplication operations of the form $\seq x = \seq a \seq b \seq c \to \seq y = \seq a \seq b…

Information Theory · Computer Science 2016-11-18 Noga Alon , Jehoshua Bruck , Farzad Farnoud , Siddharth Jain

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

We develop upper bounds on code size for an independent and identically distributed deletion and insertion channels for a given code length and target frame error probability. The bounds are obtained as a variation of a general converse…

Information Theory · Computer Science 2026-04-14 Ruslan Morozov , Tolga Mete Duman

A two-step shape reconstruction method for diffuse optical tomography (DOT) is presented which uses adjoint fields and level sets. The propagation of near-infrared photons in tissue is modeled by the time-dependent linear transport…

Numerical Analysis · Mathematics 2025-10-20 Oliver Dorn

We study near optimal error correction codes for real-time communication. In our setup the encoder must operate on an incoming source stream in a sequential manner, and the decoder must reconstruct each source packet within a fixed playback…

Information Theory · Computer Science 2013-05-16 Ahmed Badr , Ashish Khisti , Wai-Tian Tan , John Apostolopoulos

In the near future, the Internet of Things will interconnect billions of devices, forming a vast network where users sporadically transmit short messages through multi-path wireless channels. These channels are characterized by the…

Information Theory · Computer Science 2025-05-05 Sajad Daei , Saeed Razavikia , Mikael Skoglund , Gabor Fodor , Carlo Fischione

The current paper is a study in Recurrent Neural Networks (RNN), motivated by the lack of examples simple enough so that they can be thoroughly understood theoretically, but complex enough to be realistic. We constructed an example of…

Machine Learning · Statistics 2019-11-26 Marek Rychlik

Sparse channel estimation for massive multiple-input multiple-output systems has drawn much attention in recent years. The required pilots are substantially reduced when the sparse channel state vectors can be reconstructed from a few…

Information Theory · Computer Science 2021-02-17 Pengxia Wu , Hui Ma , Julian Cheng

The congested clique model is a message-passing model of distributed computation where the underlying communication network is the complete graph of $n$ nodes. In this paper we consider the situation where the joint input to the nodes is an…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-13 Pedro Montealegre , Sebastian Perez-Salazar , Ivan Rapaport , Ioan Todinca

The deletion channel is known to be a notoriously diffcult channel to design error-correction codes for. In spite of this difficulty, there are some beautiful code constructions which give some intuition about the channel and about what…

Data Structures and Algorithms · Computer Science 2019-06-20 Kedar Tatwawadi , Shubham Chandak

Codes in the Damerau--Levenshtein metric have been extensively studied recently owing to their applications in DNA-based data storage. In particular, Gabrys, Yaakobi, and Milenkovic (2017) designed a length-$n$ code correcting a single…

Information Theory · Computer Science 2023-06-30 Shuche Wang , Van Khu Vu , Vincent Y. F. Tan

Consider two remote nodes (encoder and decoder), each with a binary sequence. The encoder's sequence $X$ differs from the decoder's sequence $Y$ by a small number of edits (deletions and insertions). The goal is to construct a message $M$,…

Information Theory · Computer Science 2020-10-28 Mahed Abroshan , Ramji Venkataramanan , Albert Guillen i Fabregas

We present a method to reconstruct the initial linear-regime matter density field from the late-time non-linearly evolved density field in which we channel the output of standard first-order reconstruction to a convolutional neural network…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-23 Christopher J. Shallue , Daniel J. Eisenstein

Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. However, when dealing with high dimensional inputs, the training of RNNs becomes computational expensive due to the large number of model parameters. This hinders RNNs…

Machine Learning · Computer Science 2018-05-23 Jinmian Ye , Linnan Wang , Guangxi Li , Di Chen , Shandian Zhe , Xinqi Chu , Zenglin Xu

In this note we present a reconstructive algorithm for solving the cross-sectional pipe area from boundary measurements in a tree network with one inaccessbile end. This is equivalent to reconstructing the first order perturbation to a wave…

Analysis of PDEs · Mathematics 2019-09-13 Emilia Blåsten , Fedi Zouari , Moez Louati , Mohamed S. Ghidaoui

Computed tomography (CT) has become an essential part of modern science and medicine. A CT scanner consists of an X-ray source that is spun around an object of interest. On the opposite end of the X-ray source, a detector captures X-rays…

Image and Video Processing · Electrical Eng. & Systems 2023-09-14 Thomas Germer , Jan Robine , Sebastian Konietzny , Stefan Harmeling , Tobias Uelwer

Ternary channels can be used to model the behavior of some memory devices, where information is stored in three different levels. In this paper, error correcting coding for a ternary channel where some of the error transitions are not…

Information Theory · Computer Science 2011-05-31 Nicolas Bitouze , Alexandre Graell i Amat , Eirik Rosnes

Sequencing a DNA strand, as part of the read process in DNA storage, produces multiple noisy copies which can be combined to produce better estimates of the original strand; this is called trace reconstruction. One can reduce the error rate…

Information Theory · Computer Science 2024-08-22 Sundara Rajan Srinivasavaradhan , Sivakanth Gopi , Henry D. Pfister , Sergey Yekhanin

We consider the phylogenetic tree reconstruction problem with insertions and deletions (indels). Phylogenetic algorithms proceed under a model where sequences evolve down the model tree, and given sequences at the leaves, the problem is to…

Data Structures and Algorithms · Computer Science 2019-02-22 Arun Ganesh , Qiuyi Zhang

A common problem in the sciences is that a signal of interest is observed only indirectly, through smooth functionals of the signal whose values are then obscured by noise. In such inverse problems, the functionals dampen or entirely…

Methodology · Statistics 2012-07-04 Darren Homrighausen , Christopher R. Genovese
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