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In practice, deep neural networks have been found to be vulnerable to various types of noise, such as adversarial examples and corruption. Various adversarial defense methods have accordingly been developed to improve adversarial robustness…

Machine Learning · Computer Science 2020-12-24 Aishan Liu , Xianglong Liu , Chongzhi Zhang , Hang Yu , Qiang Liu , Dacheng Tao

Particularly motivated by DNA storage channels, we consider channels with synchronization errors modeled as insertions and deletions, along with substitutions. We focus on the case where the synchronization error process has memory and…

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

Neural networks have gained importance as the machine learning models that achieve state-of-the-art performance on large-scale image classification, object detection and natural language processing tasks. In this paper, we consider noisy…

Information Theory · Computer Science 2021-02-02 Chuteng Zhou , Quntao Zhuang , Matthew Mattina , Paul N. Whatmough

Echo State Networks (ESNs) are simplified recurrent neural network models composed of a reservoir and a linear, trainable readout layer. The reservoir is tunable by some hyper-parameters that control the network behaviour. ESNs are known to…

Neural and Evolutionary Computing · Computer Science 2018-11-06 Pietro Verzelli , Lorenzo Livi , Cesare Alippi

We show that the typical coordinate-wise encoding of multivariate ergodic source into prescribed alphabets has the entropy profile close to the convolution of the entropy profile of the source and the modular polymatroid that is determined…

Information Theory · Computer Science 2020-04-23 Michal Kupsa

Higher-order exceptional points (EPs) govern non-Hermitian system dynamics through their enriched and sharpened spectral topology, yet the intrinsic topological fragility hinders robust experimental realization. Here, we present a scalable…

This paper addresses the detection of a stochastic process in noise from irregular samples. We consider two hypotheses. The \emph{noise only} hypothesis amounts to model the observations as a sample of a i.i.d. Gaussian random variables…

Information Theory · Computer Science 2009-09-25 Walid Hachem , Eric Moulines , Francois Roueff

The Asymptotic Equipartition Property (AEP) in information theory establishes that independent and identically distributed (i.i.d.) states behave in a way that is similar to uniform states. In particular, with appropriate smoothing, for…

Quantum Physics · Physics 2025-04-24 Omar Fawzi , Li Gao , Mizanur Rahaman

As an application of generalised statistical mechanics, it is studied a possible route toward a consistent generalised information theory in terms of a family of non-extensive, non-parametric entropies $H^\pm_D(P)$. Unlike other proposals…

Information Theory · Computer Science 2021-03-23 Jesús Fuentes , Octavio Obregón

In this paper, a generalized version of dynamic ASEP is introduced, and it is shown that the process has a Markov duality property with the same process on the reversed lattice. The duality functions are multivariate $q$-Racah polynomials,…

Probability · Mathematics 2024-09-24 Wolter Groenevelt , Carel Wagenaar

We study the problem of downlink channel estimation in multi-user massive multiple input multiple output (MIMO) systems. To this end, we consider a Bayesian compressive sensing approach in which the clustered sparse structure of the channel…

Information Theory · Computer Science 2021-06-08 Mohammed Rashid , Mort Naraghi-Pour

A new stochastic order between two fading distributions is introduced. A fading channel dominates another in the ergodic capacity ordering sense, if the Shannon transform of the first is greater than that of the second at all values of…

Information Theory · Computer Science 2016-11-15 Adithya Rajan , Cihan Tepedelenlioglu

Many partially-successful attempts have been made to find the most natural discrete-variable version of Shannon's entropy power inequality (EPI). We develop an axiomatic framework from which we deduce the natural form of a discrete-variable…

Information Theory · Computer Science 2016-11-17 Saikat Guha , Jeffrey H. Shapiro , Raul Garcia-Patron Sanchez

The output distribution, when rate is above capacity, is investigated. It is shown that there is an asymptotic equipartition property (AEP) of the typical output sequences, independently of the specific codebook used, as long as the…

Information Theory · Computer Science 2009-09-01 Xiugang Wu , Liang-Liang Xie

In this paper, we examine an input-constrained erasure channel and we characterize the asymptotics of its capacity when the erasure rate is low. More specifically, for a general memoryless erasure channel with its input supported on an…

Information Theory · Computer Science 2016-05-10 Yonglong Li , Guangyue Han

Expressions for (EPI Shannon type) Divergence-Power Inequalities (DPI) in two cases (time-discrete and band-limited time-continuous) of stationary random processes are given. The new expressions connect the divergence rate of the sum of…

Information Theory · Computer Science 2016-11-17 Jacob Binia

Exceptional points (EP) are non-Hermitian spectral degeneracies where both eigenvalues and their corresponding eigenvectors coalesce. Recently, EPs have attracted a lot of attention as a means to enhance the responsivity of sensors, via the…

Applied Physics · Physics 2022-02-22 Rodion Kononchuk , Jizhe Cai , Fred Ellis , Ramathasan Thevamaran , Tsampikos Kottos

This paper presents a new derivation method of converse bounds on the non-asymptotic achievable rate of discrete weakly symmetric memoryless channels. It is based on the finite blocklength statistics of the channel, where with the use of an…

Information Theory · Computer Science 2022-02-08 Ioannis Papoutsidakis , Robert J. Piechocki , Angela Doufexi

Shannon Entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs…

Chaotic Dynamics · Physics 2016-12-08 Nithin Nagaraj , Karthi Balasubramanian

This paper considers the problem of stabilizing a discrete-time non-linear stochastic system over a finite capacity noiseless channel. Our focus is on systems which decompose into a stable and unstable component, and the stability notion…

Optimization and Control · Mathematics 2021-09-07 Nicolás Garcia , Christoph Kawan , Serdar Yüksel