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This paper investigates the information-theoretic limits of energy-harvesting (EH) channels in the finite blocklength regime. The EH process is characterized by a sequence of i.i.d. random variables with finite variances. We use the…

Information Theory · Computer Science 2016-10-19 Silas L. Fong , Vincent Y. F. Tan , Jing Yang

Memoryless channels with synchronization errors as defined by a stochastic channel matrix allowing for symbol insertions and deletions in addition to random errors are considered. Such channels are information stable, hence their Shannon…

Information Theory · Computer Science 2011-03-01 Tolga M Duman

We firstly extend the interpretation of feedback communication over stationary finite dimensional Gaussian channels as feedback control systems by showing that, the problem of finding stabilizing feedback controllers with maximal reliable…

Information Theory · Computer Science 2015-12-01 Chong Li , Nicola Elia

Universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC's)), and various ensembles of random codes, are studied by combining the competitive minimax approach,…

Information Theory · Computer Science 2007-08-01 Yaniv Akirav , Neri Merhav

As an emerging non-volatile memory (NVM) technology, spin-torque transfer magnetic random access memory (STT-MRAM) has received great attention in recent years since it combines the features of low switching energy, fast write/read speed,…

Information Theory · Computer Science 2024-10-08 Xingwei Zhong , Kui Cai , Guanghui Song

Deterministic identification over K-input multiple-access channels with average input cost constraints is considered. The capacity region for deterministic identification is determined for an average-error criterion, where arbitrarily large…

Information Theory · Computer Science 2023-06-21 Johannes Rosenberger , Abdalla Ibrahim , Christian Deppe , Roberto Ferrara

This paper introduces an upper bound on the absolute difference between: (a) the cumulative distribution function (CDF) of the sum of a finite number of independent and identically distributed random variables with finite absolute third…

Information Theory · Computer Science 2020-07-22 Dadja Anade , Jean-Marie Gorce , Philippe Mary , Samir Perlaza

The conventional channel resolvability refers to the minimum rate needed for an input process to approximate the channel output distribution in total variation distance. In this paper we study $E_{\gamma}$-resolvability, in which total…

Information Theory · Computer Science 2017-07-24 Jingbo Liu , Paul Cuff , Sergio Verdú

A conceptually simple method for derivation of lower bounds on the error exponent of specific families of block codes used on classical-quantum channels with arbitrary signal states over a finite Hilbert space is presented. It is shown that…

Quantum Physics · Physics 2007-05-23 Pawel Wocjan , Dejan E. Lazic , Thomas Beth

When information is to be transmitted over an unknown, possibly unreliable channel, an erasure option at the decoder is desirable. Using constant-composition random codes, we propose a generalization of Csiszar and Korner's Maximum Mutual…

Information Theory · Computer Science 2016-11-17 Pierre Moulin

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this…

Machine Learning · Statistics 2017-02-28 Olivier Bachem , Mario Lucic , S. Hamed Hassani , Andreas Krause

We address the estimation of the loss parameter of a bosonic channel probed by Gaussian signals. We derive the ultimate quantum bound on precision and show that no improvement may be obtained by having access to the environment degrees of…

Quantum Physics · Physics 2009-11-13 Alex Monras , Matteo G. A. Paris

The zero-error capacity of a classical channel is a parameter of its confusability graph, and is equal to the minimum of the values of graph parameters that are additive under the disjoint union, multiplicative under the strong product,…

Information Theory · Computer Science 2022-07-22 Péter Vrana

We determine a fundamental upper bound on the performance of any adaptive protocol for discrimination or estimation of a channel which has an unknown parameter encoded in the state of its environment. Since our approach relies on the…

Quantum Physics · Physics 2016-11-29 Masahiro Takeoka , Mark M. Wilde

Upper bounds on the secret-key-agreement capacity of a quantum channel serve as a way to assess the performance of practical quantum-key-distribution protocols conducted over that channel. In particular, if a protocol employs a quantum…

Quantum Physics · Physics 2018-03-13 Eneet Kaur , Mark M. Wilde

This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the…

Information Theory · Computer Science 2007-07-13 Igal Sason , Gil Wiechman

This paper proposes a statistically optimal approach for learning a function value using a confidence interval in a wide range of models, including general non-parametric estimation of an expected loss described as a stochastic programming…

Machine Learning · Statistics 2025-08-07 Arnab Ganguly , Tobias Sutter

In this work we establish universal ensemble independent bounds on the mean and variance of the mutual information and channel capacity for imaging through a complex medium. Both upper and lower bounds are derived and are solely dependent…

Optics · Physics 2020-08-20 Niall Byrnes , Matthew R. Foreman

Estimating the unitarity of an unknown quantum channel $\mathcal{E}$ provides information on how much it is unitary, which is a basic and important problem in quantum device certification and benchmarking. Unitarity estimation can be…

Quantum Physics · Physics 2026-02-23 Kean Chen , Qisheng Wang , Peixun Long , Mingsheng Ying

This paper introduces a random modulation technique that is decoupled from the channel matrix, allowing it to be applied to arbitrary norm-bounded and spectrally convergent channel matrices. The proposed random modulation constructs an…

Information Theory · Computer Science 2026-01-01 Lei Liu , Yuhao Chi , Shunqi Huang
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