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Accurate noise modelling is important for training of deep learning reconstruction algorithms. While noise models are well known for traditional imaging techniques, the noise distribution of a novel sensor may be difficult to determine a…

Machine Learning · Computer Science 2018-07-11 Felix Horger , Tobias Würfl , Vincent Christlein , Andreas Maier

To model printing noise a binary noisy channel and a set of controlled gates are introduced. The channel input is an image created by a halftoning algorithm and its output is the printed picture. Using this channel robustness to noise…

Other Computer Science · Computer Science 2015-03-19 V. N. Gorbachev , E. S. Yakovleva

The broadcast phase (downlink transmission) of the two-way relay network is studied in the source coding and joint source-channel coding settings. The rates needed for reliable communication are characterised for a number of special cases…

Information Theory · Computer Science 2010-11-23 Roy Timo , Alex Grant , Gerhard Kramer

A transmitter Alice may wish to reliably transmit a message to a receiver Bob over a binary symmetric channel (BSC), while simultaneously ensuring that her transmission is deniable from an eavesdropper Willie. That is, if Willie listening…

Information Theory · Computer Science 2016-07-12 Pak Hou Che , Mayank Bakshi , Sidharth Jaggi

We consider the transmission of nonexponentially many messages through a binary symmetric channel with noiseless feedback. We obtain an upper bound for the best decoding error exponent. Combined with the corresponding known lower bound,…

Information Theory · Computer Science 2022-10-14 Marat V. Burnashev

We extend quantum rate distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate distortion coding…

Quantum Physics · Physics 2013-12-09 Mark M. Wilde , Nilanjana Datta , Min-Hsiu Hsieh , Andreas Winter

The design of codes for communicating reliably over a statistically well defined channel is an important endeavor involving deep mathematical research and wide-ranging practical applications. In this work, we present the first family of…

Machine Learning · Computer Science 2018-07-03 Hyeji Kim , Yihan Jiang , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

Recurrent neural networks (RNNs) provide state-of-the-art performance in processing sequential data but are memory intensive to train, limiting the flexibility of RNN models which can be trained. Reversible RNNs---RNNs for which the…

Machine Learning · Computer Science 2018-10-26 Matthew MacKay , Paul Vicol , Jimmy Ba , Roger Grosse

This paper develops tools to obtain robust probabilistic estimates for queueing models at the large deviations (LD) scale. These tools are based on the recently introduced robust R\'enyi bounds, which provide LD estimates (and more…

Probability · Mathematics 2020-08-14 Rami Atar , Amarjit Budhiraja , Paul Dupuis , Ruoyu Wu

We show that the communication cost of quantum broadcast channel simulation under free entanglement assistance between the sender and the receivers is asymptotically characterized by an efficiently computable single-letter formula in terms…

Quantum Physics · Physics 2023-05-05 Hao-Chung Cheng , Li Gao , Mario Berta

We study the effect of shared non-signaling correlations for the problem of simulating a channel using noiseless communication in the one-shot setting. For classical channels, we show how to round any non-signaling-assisted simulation…

Quantum Physics · Physics 2024-11-18 Aadil Oufkir , Omar Fawzi , Mario Berta

Shannon's channel coding theorem characterizes the maximal rate of information that can be reliably transmitted over a communication channel when optimal encoding and decoding strategies are used. In many scenarios, however, practical…

Information Theory · Computer Science 2023-07-06 Jonathan Scarlett , Albert Guillén i Fàbregas , Anelia Somekh-Baruch , Alfonso Martinez

New channel coding converse and achievability bounds are derived for a single use of an arbitrary channel. Both bounds are expressed using a quantity called the "smooth 0-divergence", which is a generalization of Renyi's divergence of order…

Information Theory · Computer Science 2010-07-29 Ligong Wang , Roger Colbeck , Renato Renner

Inverse problems arise in a multitude of applications, where the goal is to recover a clean signal from noisy and possibly (non)linear observations. The difficulty of a reconstruction problem depends on multiple factors, such as the ground…

Image and Video Processing · Electrical Eng. & Systems 2024-08-21 Zalan Fabian , Berk Tinaz , Mahdi Soltanolkotabi

The rational large eddy simulation (RLES) model is applied to turbulent channel flows. This approximate deconvolution model is based on a rational (subdiagonal Pade') approximation of the Fourier transform of the Gaussian filter and is…

Numerical Analysis · Mathematics 2025-10-20 T. Iliescu , P. Fischer

We consider the discrete memoryless degraded broadcast channels with feedback. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this…

Information Theory · Computer Science 2015-04-24 Yasutada Oohama

We derive a lower bound on the differential entropy of a log-concave random variable $X$ in terms of the $p$-th absolute moment of $X$. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds…

Information Theory · Computer Science 2018-04-04 Arnaud Marsiglietti , Victoria Kostina

We consider the problem of implementing two-party interactive quantum communication over noisy channels, a necessary endeavor if we wish to fully reap quantum advantages for communication. For an arbitrary protocol with $n$ messages,…

Quantum Physics · Physics 2020-01-10 Debbie Leung , Ashwin Nayak , Ala Shayeghi , Dave Touchette , Penghui Yao , Nengkun Yu

Rodrigo de Miguel et al 2007 J. Phys. A: Math. Theor. 40 5241-5260: A noisy vector channel operating under a strict complexity constraint at the receiver is introduced. According to this constraint, detected bits, obtained by performing…

Information Theory · Computer Science 2009-11-11 Rodrigo de Miguel , Ori Shental , Ralf R. Muller , Ido Kanter

R\'enyi divergence is related to R\'enyi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes up in many settings. It was introduced by R\'enyi as a measure of information that satisfies almost the same…

Information Theory · Computer Science 2014-04-25 Tim van Erven , Peter Harremoës
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