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We investigate weakly constrained codes, in which specific patterns occur with prescribed frequencies rather than being strictly forbidden as in conventional constrained coding. We propose a capacity-achieving construction of a weakly…

Information Theory · Computer Science 2026-05-22 Prachi Mishra , Sidharth Jaggi , Navin Kashyap , Michael Langberg

In this work, we study linear error-correcting codes against adversarial insertion-deletion (indel) errors. While most constructions for the indel model are nonlinear, linear codes offer compact representations, efficient encoding, and…

Information Theory · Computer Science 2025-10-01 Roee Gross , Roni Con , Eitan Yaakobi

In this paper, we study binary constrained codes that are resilient to bit-flip errors and erasures. In our first approach, we compute the sizes of constrained subcodes of linear codes. Since there exist well-known linear codes that achieve…

Information Theory · Computer Science 2023-04-20 V. Arvind Rameshwar , Navin Kashyap

Run length limited (RLL) codes are used in visible light communication (VLC) to avoid flicker and to support different dimming ranges such that communication is not affected by the variation in light intensity. In this paper, we propose a…

Information Theory · Computer Science 2019-06-06 Nitin Jain , Adrish Banerjee

Deep learning (DL) techniques are increasingly pervasive across various domains, including wireless communication, where they extract insights from raw radio signals. However, the computational demands of DL pose significant challenges,…

Signal Processing · Electrical Eng. & Systems 2024-09-05 Dieter Verbruggen , Hazem Sallouha , Sofie Pollin

Lossless floating-point time series compression is crucial for a wide range of critical scenarios. Nevertheless, it is a big challenge to compress time series losslessly due to the complex underlying layouts of floating-point values. The…

Data Structures and Algorithms · Computer Science 2023-09-15 Ruiyuan Li , Zheng Li , Yi Wu , Chao Chen , Tong Liu , Yu Zheng

The error pattern correcting code (EPCC) can be constructed to provide a syndrome decoding table targeting the dominant error events of an inter-symbol interference channel at the output of the Viterbi detector. For the size of the syndrome…

Information Theory · Computer Science 2010-03-31 Hakim Alhussien , Jaekyun Moon

We introduce the "exponential linear unit" (ELU) which speeds up learning in deep neural networks and leads to higher classification accuracies. Like rectified linear units (ReLUs), leaky ReLUs (LReLUs) and parametrized ReLUs (PReLUs), ELUs…

Machine Learning · Computer Science 2016-02-23 Djork-Arné Clevert , Thomas Unterthiner , Sepp Hochreiter

In this paper, we introduce a deep learning-based decoder designed for concatenated coding schemes over a deletion/substitution channel. Specifically, we focus on serially concatenated codes, where the outer code is either a convolutional…

Information Theory · Computer Science 2024-10-15 E. Uras Kargı , Tolga M. Duman

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

We introduce and study exterior distance function (EDF) and correspondent exterior point method (EPM) for convex optimization. The EDF is a classical Lagrangian for an equivalent problem obtained from the initial one by monotone…

Optimization and Control · Mathematics 2017-06-28 Roman Polyak

The rapid growth of nature-inspired metaheuristics has exposed a persistent gap between metaphorical novelty and genuine algorithmic advancement. Motivated by the biophysics of chromatin loop extrusion -- a well-characterized genome-folding…

Neural and Evolutionary Computing · Computer Science 2026-04-07 Eren Unlu

In this work, we prove new results concerning the combinatorial properties of random linear codes. Firstly, we prove a lower bound on the list-size required for random linear codes over $\mathbb F_q$ $\varepsilon$-close to capacity to…

Information Theory · Computer Science 2022-05-04 Nicolas Resch , Chen Yuan

Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes (SC-TCs) with excellent belief propagation (BP) thresholds. In this paper, we analyze the performance of BCCs in the finite block-length regime. We derive…

Information Theory · Computer Science 2016-08-09 Saeedeh Moloudi , Michael Lentmaier , Alexandre Graell i Amat

A Maximum Distance Separable code over an alphabet $F$ is defined via an encoding function $C:F^k \rightarrow F^n$ that allows to retrieve a message $m \in F^k$ from the codeword $C(m)$ even after erasing any $n-k$ of its symbols. The…

Information Theory · Computer Science 2020-05-15 Mira Gonen , Ishay Haviv , Michael Langberg , Alex Sprintson

We derive the optimum second-order coding rates, known as second-order capacities, for erasure and list decoding. For erasure decoding for discrete memoryless channels, we show that second-order capacity is $\sqrt{V}\Phi^{-1}(\epsilon_t)$…

Information Theory · Computer Science 2014-04-22 Vincent Y. F. Tan , Pierre Moulin

Linear computation coding is concerned with the compression of multidimensional linear functions, i.e. with reducing the computational effort of multiplying an arbitrary vector to an arbitrary, but known, constant matrix. This paper…

Information Theory · Computer Science 2025-07-02 Hans Rosenberger , Johanna S. Fröhlich , Ali Bereyhi , Ralf R. Müller

Locally Decodable Codes (LDCs) are error-correcting codes for which individual message symbols can be quickly recovered despite errors in the codeword. LDCs for Hamming errors have been studied extensively in the past few decades, where a…

Information Theory · Computer Science 2025-12-30 Jeremiah Blocki , Kuan Cheng , Elena Grigorescu , Xin Li , Yu Zheng , Minshen Zhu

Raptor code ensembles with linear random outer codes in a fixed-rate setting are considered. An expression for the average distance spectrum is derived and this expression is used to obtain the asymptotic exponent of the weight…

Information Theory · Computer Science 2015-11-03 Francisco Lázaro , Enrico Paolini , Gianluigi Liva , Gerhard Bauch

The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially…

Information Theory · Computer Science 2016-11-17 Neri Merhav