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A general class of polynomial remainder codes is considered. Such codes are very flexible in rate and length and include Reed-Solomon codes as a special case. As an extension of previous work, two joint error-and-erasure decoding approaches…

Information Theory · Computer Science 2012-02-27 Jiun-Hung Yu

In this paper, parameterized Gallager's first bounding technique (GFBT) is presented by introducing nested Gallager regions, to derive upper bounds on the ML decoding error probability of general codes over AWGN channels. The three…

Information Theory · Computer Science 2013-12-30 Qiutao Zhuang , Jia Liu , Xiao Ma

This paper provides a dual domain derivation of the error exponent of maximum mutual information (MMI) decoding with constant composition codes, showing it coincides with that of maximum likelihood decoding for discrete memoryless channels.…

Information Theory · Computer Science 2025-07-25 AmirPouya Moeini , Albert Guillén i Fàbregas

Generalized cross-validation (GCV) is a widely-used method for estimating the squared out-of-sample prediction risk that employs a scalar degrees of freedom adjustment (in a multiplicative sense) to the squared training error. In this…

Statistics Theory · Mathematics 2024-04-23 Pierre C. Bellec , Jin-Hong Du , Takuya Koriyama , Pratik Patil , Kai Tan

We consider the rate distortion problem with side information at the decoder posed and investigated by Wyner and Ziv. The rate distortion function indicating the trade-off between the rate on the data compression and the quality of data…

Information Theory · Computer Science 2016-04-27 Yasutada Oohama

We propose a general error analysis related to the low-rank approximation of a given real matrix in both the spectral and Frobenius norms. First, we derive deterministic error bounds that hold with some minimal assumptions. Second, we…

Numerical Analysis · Mathematics 2022-06-22 Youssef Diouane , Selime Gürol , Alexandre Scotto Di Perrotolo , Xavier Vasseur

We consider the topic of universal decoding with a decoder that does not have direct access to the codebook, but only to noisy versions of the various randomly generated codewords, a problem motivated by biometrical identification systems.…

Information Theory · Computer Science 2016-09-05 Neri Merhav

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

We provide sharp path-dependent generalization and excess risk guarantees for the full-batch Gradient Descent (GD) algorithm on smooth losses (possibly non-Lipschitz, possibly nonconvex). At the heart of our analysis is an upper bound on…

Machine Learning · Statistics 2023-02-13 Konstantinos E. Nikolakakis , Farzin Haddadpour , Amin Karbasi , Dionysios S. Kalogerias

Error and erasure exponents for the broadcast channel with degraded message sets are analyzed. The focus of our error probability analysis is on the main receiver where, nominally, both messages are to be decoded. A two-step decoding…

Information Theory · Computer Science 2015-01-28 Vincent Y. F. Tan

We consider ensembles of channel codes that are partitioned into bins, and focus on analysis of exact random coding error exponents associated with optimum decoding of the index of the bin to which the transmitted codeword belongs. Two main…

Information Theory · Computer Science 2016-11-18 Neri Merhav

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

In this paper, we consider a concatenated coding based class of DNA storage codes in which the selected molecules are constrained to be taken from an ``inner'' codebook associated with the sequencing channel. This codebook is used in a…

Information Theory · Computer Science 2025-06-19 Yan Hao Ling , Jonathan Scarlett

In this work, we study the generalization capability of algorithms from an information-theoretic perspective. It has been shown that the expected generalization error of an algorithm is bounded from above by a function of the relative…

Information Theory · Computer Science 2021-10-27 Borja Rodríguez-Gálvez , Germán Bassi , Mikael Skoglund

In this paper, we analyze the tradeoff between coding rate and asymptotic performance of a class of generalized low-density parity-check (GLDPC) codes constructed by including a certain fraction of generalized constraint (GC) nodes in the…

Information Theory · Computer Science 2019-10-16 Yanfang Liu , Pablo M. Olmos , Tobias Koch

We investigate threshold-based multi-trial decoding of concatenated codes with an inner Maximum-Likelihood decoder and an outer error/erasure (L+1)/L-extended Bounded Distance decoder, i.e. a decoder which corrects e errors and t erasures…

Information Theory · Computer Science 2012-02-07 Christian Senger , Vladimir R. Sidorenko , Martin Bossert , Victor V. Zyablov

In this paper, we investigate the performance of the Viterbi decoding algorithm with/without Automatic Repeat reQuest (ARQ) over a Rician flat fading channel with unlimited interleaving. We show that the decay rate of the average bit error…

Information Theory · Computer Science 2018-10-05 Lan V. Truong

This paper is concerned with the lossy compression of general random variables, specifically with rate-distortion theory and quantization of random variables taking values in general measurable spaces such as, e.g., manifolds and fractal…

Probability · Mathematics 2023-06-05 Erwin Riegler , Helmut Bölcskei , Günther Koliander

Given finite-dimensional random vectors $Y$, $X$, and $Z$ that form a Markov chain in that order (i.e., $Y \to X \to Z$), we derive upper bounds on the excess minimum risk using generalized information divergence measures. Here, $Y$ is a…

Information Theory · Computer Science 2025-06-02 Ananya Omanwar , Fady Alajaji , Tamás Linder

We compute the code parameters for binary linear codes obtained by greedy constructing the parity check matrix. Then we show that these codes improve the Gilbert-Varshamov (GV) bound on the code size and rate. This result counter proves the…

Information Theory · Computer Science 2009-03-12 Dejan Spasov , Marjan Gusev
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