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Related papers: New Non-asymptotic Random Channel Coding Theorems

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This paper revisits the Gaussian degraded relay channel, where the link that carries information from the source to the destination is a physically degraded version of the link that carries information from the source to the relay. The…

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

The ultimate limits of quantum state discrimination are often thought to be captured by asymptotic bounds that restrict the achievable error probabilities, notably the quantum Chernoff and Hoeffding bounds. Here we study hypothesis testing…

Quantum Physics · Physics 2025-12-10 Kaiyuan Ji , Bartosz Regula

We consider the problem of synthesizing joint distributions of signals and actions over noisy channels in the finite-length regime. For a fixed blocklength $n$ and an upper bound on the distance $\varepsilon$, a coding scheme is proposed…

Information Theory · Computer Science 2019-09-30 Giulia Cervia , Tobias Oechtering , Mikael Skoglund

For the discrete-time additive white generalized Gaussian noise channel with a generalized input power constraint, with the respective shape and power parameters >= 1, we derive an upper bound on the optimal block error exponent. Explicit…

Information Theory · Computer Science 2025-09-11 Sergey Tridenski , Anelia Somekh-Baruch

This paper shows that the logarithm of the epsilon-error capacity (average error probability) for n uses of a discrete memoryless channel is upper bounded by the normal approximation plus a third-order term that does not exceed 1/2 log n +…

Information Theory · Computer Science 2013-10-25 Marco Tomamichel , Vincent Y. F. Tan

A new framework is introduced for examining and evaluating the fundamental limits of lossless data compression, that emphasizes genuinely non-asymptotic results. The {\em sample complexity} of compressing a given source is defined as the…

Information Theory · Computer Science 2026-04-16 Terence Viaud , Ioannis Kontoyiannis

We study quantum versions of the Shannon capacity of graphs and non-commutative graphs. We introduce the asymptotic spectrum of graphs with respect to quantum and entanglement-assisted homomorphisms, and we introduce the asymptotic spectrum…

Quantum Physics · Physics 2020-10-20 Yinan Li , Jeroen Zuiddam

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is…

Information Theory · Computer Science 2016-09-19 Victoria Kostina , Sergio Verdú

We study non-asymptotic fundamental limits for transmitting classical information over memoryless quantum channels, i.e. we investigate the amount of classical information that can be transmitted when a quantum channel is used a finite…

Quantum Physics · Physics 2015-05-20 Marco Tomamichel , Vincent Y. F. Tan

We consider the sequential composite binary hypothesis testing problem in which one of the hypotheses is governed by a single distribution while the other is governed by a family of distributions whose parameters belong to a known set…

Information Theory · Computer Science 2022-03-30 Jiachun Pan , Yonglong Li , Vincent Y. F. Tan

We consider a point-to-point communication system, where in addition to the encoder and the decoder, there is a helper that observes non-causally the realization of the noise vector and provides a (lossy) rate-$R_{\mbox{\tiny h}}$…

Information Theory · Computer Science 2020-11-23 Neri Merhav

Given a sufficient statistic for a parametric family of distributions, one can estimate the parameter without access to the data. However, the memory or code size for storing the sufficient statistic may nonetheless still be prohibitive.…

Information Theory · Computer Science 2017-11-17 Masahito Hayashi , Vincent Y. F. Tan

We prove non-asymptotic error bounds for Sequential MCMC methods in the case of multimodal target distributions. Our bounds depend in an explicit way on upper bounds on relative densities, on constants associated with local mixing…

Probability · Mathematics 2012-05-31 Nikolaus Schweizer

This paper considers the estimation of Shannon entropy for discrete distributions with countably infinite support. While minimax rates for finite-support distributions are established, infinite-support distributions present distinct…

Statistics Theory · Mathematics 2025-12-03 Octavio César Mesner

We leverage proof techniques Fourier analysis and an existing result in coding theory to derive new bounds for the problem of non-interactive simulation of binary random variables. Previous bounds in the literature were derived by applying…

Information Theory · Computer Science 2021-01-26 Lei Yu , Vincent Y. F. Tan

It is well known that orthogonal coding can be used to approach the Shannon capacity of the power-constrained AWGN channel without a bandwidth constraint. This correspondence describes a semi-orthogonal variation of pulse position…

Information Theory · Computer Science 2007-07-13 Anant Sahai

We introduce a new computational model for data streams: asymptotically exact streaming algorithms. These algorithms have an approximation ratio that tends to one as the length of the stream goes to infinity while the memory used by the…

Data Structures and Algorithms · Computer Science 2014-08-11 Marc Heinrich , Alexander Munteanu , Christian Sohler

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph

Channel symmetry properties that imply the tightness of Shannon's random coding inner bound have recently been used to determine the capacity region of discrete-memoryless two-way channels (DM-TWCs). For channels without such symmetry…

Information Theory · Computer Science 2020-09-28 Jian-Jia Weng , Fady Alajaji , Tamás Linder

A coding theorem is proved for a class of stationary channels with feedback in which the output Y_n = f(X_{n-m}^n, Z_{n-m}^n) is the function of the current and past m symbols from the channel input X_n and the stationary ergodic channel…

Information Theory · Computer Science 2007-07-13 Young-Han Kim
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