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We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

We consider transmission of stationary and ergodic sources over non-ergodic composite channels with channel state information at the receiver (CSIR). Previously we introduced alternate capacity definitions to Shannon capacity, including the…

Information Theory · Computer Science 2009-02-27 Yifan Liang , Andrea Goldsmith , Michelle Effros

In this monograph, we review recent advances in second-order asymptotics for lossy source coding, which provides approximations to the finite blocklength performance of optimal codes. The monograph is divided into three parts. In part I, we…

Information Theory · Computer Science 2024-10-25 Lin Zhou , Mehul Motani

The error exponent in lossy source coding characterizes the asymptotic decay rate of error probability with respect to blocklength. The Marton's error exponent provides the theoretically optimal bound on this rate. However, computation…

Information Theory · Computer Science 2025-07-29 Jiachuan Ye , Shitong Wu , Lingyi Chen , Wenyi Zhang , Huihui Wu , Hao Wu

We consider three capacity definitions for general channels with channel side information at the receiver, where the channel is modeled as a sequence of finite dimensional conditional distributions not necessarily stationary, ergodic, or…

Information Theory · Computer Science 2016-11-17 Michelle Effros , Andrea Goldsmith , Yifan Liang

The minimum average number of bits need to describe a random variable is its entropy, assuming knowledge of the underlying statistics On the other hand, universal compression supposes that the distribution of the random variable, while…

Information Theory · Computer Science 2014-04-02 Maryam Hosseini , Narayana Santhanam

Second order asymptotics of fixed-length source coding and intrinsic randomness is discussed with a constant error constraint. There was a difference between optimal rates of fixed-length source coding and intrinsic randomness, which never…

Information Theory · Computer Science 2010-01-23 Masahito Hayashi

The reliability function of memoryless channels with noiseless feedback and variable-length coding has been found to be a linear function of the average rate in the classic work of Burnashev. In this work we consider unifilar channels with…

Information Theory · Computer Science 2017-07-11 Achilleas Anastasopoulos , Jui Wu

This paper investigates an energy-efficient non-orthogonal transmission design problem for two downlink receivers that have strict reliability and finite blocklength (latency) constraints. The Shannon capacity formula widely used in…

Information Theory · Computer Science 2017-12-14 Yanqing Xu , Chao Shen , Tsung-Hui Chang , Shih-Chun Lin , Yajun Zhao , Gang Zhu

Learning and decision making in the brain are key processes critical to survival, and yet are processes implemented by non-ideal biological building blocks which can impose significant error. We explore quantitatively how the brain might…

Neurons and Cognition · Quantitative Biology 2011-04-19 Jake Bouvrie , Jean-Jacques Slotine

A source encoder is stable if a small change in the source sequence (e.g., changing a few symbols) results in a small (or bounded) change in the output codeword. By this definition, the common technique of random binning is unstable;…

Information Theory · Computer Science 2026-01-26 Zhenduo Wen , Amin Gohari

Single Event Upsets (SEU) as well as permanent faults can significantly affect the correct on-line operation of digital systems, such as memories and microprocessors; a memory can be made resilient to permanent and transient faults by using…

Information Theory · Computer Science 2011-11-09 L. Schiano , M. Ottavi , F. Lombardi , S. Pontarelli , A. Salsano

We study sequential coding of Markov sources under an error propagation constraint. An encoder sequentially compresses a sequence of vector-sources that are spatially i.i.d. but temporally correlated according to a first-order Markov…

Information Theory · Computer Science 2012-02-24 Farrokh Etezadi , Ashish Khisti , Mitchell Trott

In distributed computing systems with stragglers, various forms of redundancy can improve the average delay performance. We study the optimal replication of data in systems where the job execution time is a stochastically decreasing and…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-01 Amir Behrouzi-Far , Emina Soljanin

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

Higher-order information theory has become a rapidly growing toolkit in computational neuroscience, motivated by the idea that multivariate dependencies can reveal aspects of neural computation and communication that are invisible to…

Neurons and Cognition · Quantitative Biology 2025-12-03 D. Rebbin , K. J. A. Down , T. F. Varley , R. Ince , A. Canales-Johnson

The recently proposed set-up of source coding with a side information "vending machine" allows the decoder to select actions in order to control the quality of the side information. The actions can depend on the message received from the…

Information Theory · Computer Science 2013-01-08 Osvaldo Simeone

Consider communication over a channel whose probabilistic model is completely unknown vector-wise and is not assumed to be stationary. Communication over such channels is challenging because knowing the past does not indicate anything about…

Information Theory · Computer Science 2013-03-21 Yuval Lomnitz , Meir Feder

We derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process when the channel is a discrete memoryless, while a previous study solved it only in a special case. We also…

Information Theory · Computer Science 2024-09-10 Ryo Yaguchi , Masahito Hayashi

We investigate the stopping redundancy hierarchy of linear block codes and its connection to permutation decoding techniques. An element in the ordered list of stopping redundancy values represents the smallest number of possibly linearly…

Information Theory · Computer Science 2007-07-13 Thorsten Hehn , Olgica Milenkovic , Stefan Laendner , Johannes B. Huber
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