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Consider the problem of identifying a massive number of bees, uniquely labeled with barcodes, using noisy measurements. We formally introduce this `bee-identification problem', define its error exponent, and derive efficiently computable…

Information Theory · Computer Science 2019-06-05 Anshoo Tandon , Vincent Y. F. Tan , Lav R. Varshney

We consider the one helper source coding problem posed and investigated by Ahlswede, K\"orner and Wyner. In this system, the error probability of decoding goes to one as the source block length $n$ goes to infinity. This implies that we…

Information Theory · Computer Science 2019-01-18 Yasutada Oohama

A new straightforward universal blind detection algorithm for linear Gaussian channel with ISI is given. A new error exponent is derived, which is better than Gallager's random coding error exponent.

Information Theory · Computer Science 2008-01-04 Lóránt Farkas

This article studies the achievable guarantees on the error rates of certain learning algorithms, with particular focus on refining logarithmic factors. Many of the results are based on a general technique for obtaining bounds on the error…

Machine Learning · Computer Science 2016-09-13 Steve Hanneke

Inner and outer bounds are derived on the optimal performance of fixed length block codes on discrete memoryless channels with feedback and errors-and-erasures decoding. First an inner bound is derived using a two phase encoding scheme with…

Information Theory · Computer Science 2020-01-03 Baris Nakiboglu , Lizhong Zheng

We analyze the optimal trade-off between the error exponent and the excess-rate exponent for variable-rate Slepian-Wolf codes. In particular, we first derive upper (converse) bounds on the optimal error and excess-rate exponents, and then…

Information Theory · Computer Science 2014-11-07 Nir Weinberger , Neri Merhav

This paper studies expurgated exponents for joint source-channel coding of discrete memoryless sources and channels under i.i.d. random coding. We show that a two-class partitioning of source sequences, where the codeword distribution…

Information Theory · Computer Science 2026-01-22 Seyed AmirPouya Moeini , Albert Guillén i Fàbregas

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

Most existing works of polar codes focus on the analysis of block error probability. However, in many scenarios, bit error probability is also important for evaluating the performance of channel codes. In this paper, we establish a new…

Information Theory · Computer Science 2022-04-18 Bolin Wu , Kai Niu , Jincheng Dai

We consider the discrete memoryless degraded broadcast channels with feedback. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this…

Information Theory · Computer Science 2015-04-24 Yasutada Oohama

We investigate the achievable error probability in communication over an AWGN discrete time memoryless channel with noiseless delay-less rate-limited feedback. For the case where the feedback rate R_FB is lower than the data rate R…

Information Theory · Computer Science 2012-04-24 Reza Mirghaderi , Andrea Goldsmith , Tsachy Weissman

We analyze random coding error exponents associated with erasure/list Slepian-Wolf decoding using two different methods and then compare the resulting bounds. The first method follows the well known techniques of Gallager and Forney and the…

Information Theory · Computer Science 2013-05-27 Neri Merhav

Efficient high-performance decoding of topological stabilizer codes has the potential to crucially improve the balance between logical failure rates and the number and individual error rates of the constituent qubits. High-threshold…

In this paper q-ary Raptor codes under ML decoding are considered. An upper bound on the probability of decoding failure is derived using the weight enumerator of the outer code, or its expected weight enumerator if the outer code is drawn…

Information Theory · Computer Science 2016-11-21 Francisco Lázaro , Gianluigi Liva , Enrico Paolini , Gerhard Bauch

We study prediction and estimation problems using empirical risk minimization, relative to a general convex loss function. We obtain sharp error rates even when concentration is false or is very restricted, for example, in heavy-tailed…

Machine Learning · Statistics 2014-10-14 Shahar Mendelson

In this paper, the authors report a way to use concepts from statistical learning to gain an advantage in terms of error exponents while communicating over a discrete memoryless channel. The study utilizes the simulation capability of the…

Information Theory · Computer Science 2022-08-09 Aman Chawla , Salvatore Domenic Morgera

An erasure channel with a fixed alphabet size $q$, where $q \gg 1$, is studied. It is proved that over any erasure channel (with or without memory), Maximum Distance Separable (MDS) codes achieve the minimum probability of error (assuming…

Information Theory · Computer Science 2008-06-06 Shervan Fashandi , Shahab Oveis Gharan , Amir K. Khandani

The decoding error probability of codes is studied as a function of their block length. It is shown that the existence of codes with a polynomially small decoding error probability implies the existence of codes with an exponentially small…

Information Theory · Computer Science 2007-07-13 Alexei Ashikhmin , Vitaly Skachek

In this paper, we present an error-trellis construction for tailbiting convolutional codes. A tailbiting error-trellis is characterized by the condition that the syndrome former starts and ends in the same state. We clarify the…

Information Theory · Computer Science 2012-01-24 Masato Tajima , Koji Okino

We derive critical noise levels for Gallager codes on asymmetric channels as a function of the input bias and the temperature. Using a statistical mechanics approach we study the space of codewords and the entropy in the various decoding…

Disordered Systems and Neural Networks · Physics 2009-11-13 I. Neri , N. S. Skantzos , D. Bollé