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We compare the performance of short-length linear binary codes on the binary erasure channel and the binary-input Gaussian channel. We use a universal decoder that can decode any linear binary block code: Gaussian-elimination based…

Information Theory · Computer Science 2016-11-09 J. Van Wonterghem , A. Alloum , J. J. Boutros , M. Moeneclaey

The 3D MIMO code is a robust and efficient space-time coding scheme for the distributed MIMO broadcasting. However, it suffers from the high computational complexity if the optimal maximum-likelihood (ML) decoding is used. In this paper we…

Information Theory · Computer Science 2014-01-08 Ming Liu , Jean-François Hélard , Matthieu Crussière , Maryline Hélard

We show that the mean-model parameter is always orthogonal to the error distribution in generalized linear models. Thus, the maximum likelihood estimator of the mean-model parameter will be asymptotically efficient regardless of whether the…

Methodology · Statistics 2020-10-08 Alan Huang , Paul J. Rathouz

We derive the optimal exponent of the error probability of the quantum fixed-length pure state source coding in both cases of blind coding and visible coding. The optimal exponent is universally attained by Jozsa et al. (PRL, 81, 1714…

Quantum Physics · Physics 2009-11-07 Masahito Hayashi

Arbitrarily long quantum computations require quantum memories that can be repeatedly measured without being corrupted. Here, we preserve the state of a quantum memory, notably with the additional use of flagged error events. All error…

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

Motivated by applications of rateless coding, decision feedback, and ARQ, we study the problem of universal decoding for unknown channels, in the presence of an erasure option. Specifically, we harness the competitive minimax methodology…

Information Theory · Computer Science 2007-07-13 Neri Merhav , Meir Feder

This paper studies the theory of linear analog error correction coding. Since classical concepts of minimum Hamming distance and minimum Euclidean distance fail in the analog context, a new metric, termed the "minimum (squared Euclidean)…

Information Theory · Computer Science 2011-05-10 Kai Xie , Jing , Li

Coding and testing schemes for binary hypothesis testing over noisy networks are proposed and their corresponding type-II error exponents are derived. When communication is over a discrete memoryless channel (DMC), our scheme combines…

Information Theory · Computer Science 2018-06-15 Sadaf Salehkalaibar , Michele Wigger

Precoding for multiple-input, multiple-output (MIMO) antenna systems is considered with perfect channel knowledge available at both the transmitter and the receiver. For 2 transmit antennas and QAM constellations, an approximately optimal…

Information Theory · Computer Science 2015-03-17 K. Pavan Srinath , B. Sundar Rajan

The code that combines channel estimation and error protection has received general attention recently, and has been considered a promising methodology to compensate multi-path fading effect. It has been shown by simulations that such code…

Information Theory · Computer Science 2007-12-18 Chia-Lung Wu , Po-Ning Chen , Yunghsiang S. Han , Ming-Hsin Kuo

In this paper, random coding error exponents and cutoff rate are studied for noncoherent Rician fading channels, where neither the receiver nor the transmitter has channel side information. First, it is assumed that the input is subject…

Information Theory · Computer Science 2016-11-18 Mustafa Cenk Gursoy

Mutual information (MI) is a fundamental measure of statistical dependence between two variables, yet accurate estimation from finite data remains notoriously difficult. No estimator is universally reliable, and common approaches fail in…

Data Analysis, Statistics and Probability · Physics 2025-10-02 Eslam Abdelaleem , K. Michael Martini , Ilya Nemenman

In contrast to a maximum-likelihood decoder, it is often desirable to use an incomplete decoder that can detect its decoding errors with high probability. One common choice is the bounded distance decoder. Bounds are derived for the total…

Information Theory · Computer Science 2012-07-26 Kenneth Andrews , Sam Dolinar

Existing two-sample testing techniques, particularly those based on choosing a kernel for the Maximum Mean Discrepancy (MMD), often assume equal sample sizes from the two distributions. Applying these methods in practice can require…

Machine Learning · Statistics 2025-12-17 Aaron Wei , Milad Jalali , Danica J. Sutherland

We present a two-step decoder for the parity code and evaluate its performance in code-capacity and faulty-measurement settings. For noiseless measurements, we find that the decoding problem can be reduced to a series of repetition codes…

The following detection problem is studied, in which there are $M$ sequences of samples out of which one outlier sequence needs to be detected. Each typical sequence contains $n$ independent and identically distributed (i.i.d.) continuous…

Information Theory · Computer Science 2015-10-08 Yuheng Bu , Shaofeng Zou , Yingbin Liang , Venugopal V. Veeravalli

Asymptotic expressions of the mutual information between any discrete input and the corresponding output of the scalar additive white Gaussian noise channel are presented in the limit as the signal-to-noise ratio (SNR) tends to infinity.…

Information Theory · Computer Science 2014-04-23 Alex Alvarado , Fredrik Brannstrom , Erik Agrell , Tobias Koch

Undersampled inverse problems occur everywhere in the sciences including medical imaging, radar, astronomy etc., yielding underdetermined linear or non-linear reconstruction problems. There are now a myriad of techniques to design decoders…

Optimization and Control · Mathematics 2023-11-29 Nina Maria Gottschling , Paolo Campodonico , Vegard Antun , Anders C. Hansen

This work studies the deviations of the error exponent of the constant composition code ensemble around its expectation, known as the error exponent of the typical random code (TRC). In particular, it is shown that the probability of…

Information Theory · Computer Science 2019-12-23 Ran Tamir , Neri Merhav , Nir Weinberger , Albert Guillen i Fabregas