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In the short block length regime, pre-transformed polar codes together with successive cancellation list (SCL) decoding possess excellent error correction capabilities. However, in practice, the list size is limited due to the suboptimal…

Information Theory · Computer Science 2025-04-25 Henning Lulei , Jonathan Mandelbaum , Marvin Rübenacke , Holger Jäkel , Stephan ten Brink , Laurent Schmalen

The security of code-based cryptography relies primarily on the hardness of generic decoding with linear codes. The best generic decoding algorithms are all improvements of an old algorithm due to Prange: they are known under the name of…

Cryptography and Security · Computer Science 2017-02-09 Thomas Debris-Alazard , Jean-Pierre Tillich

In this paper, we construct new families of convolutional codes. Such codes are obtained by means of algebraic geometry codes. Additionally, more families of convolutional codes are constructed by means of puncturing, extending, expanding…

Information Theory · Computer Science 2021-07-27 Francisco Revson F. Pereira , Giuliano G. La Guardia , Francisco M. de Assis

We propose a new type of ultimate-Shannon-limit-approaching codes called spatially coupled protograph-based low-density parity-check Hadamard convolutional codes (SC-PLDPCH-CCs), which are constructed by spatially coupling PLDPC-Hadamard…

Information Theory · Computer Science 2022-07-26 Peng W. Zhang , Francis C. M. Lau , Chiu-W. Sham

Multimodal optimization requires finding many optima rather than merely keeping a diverse population. Yet most niching-based evolutionary algorithms rely on distances or density estimators without explicitly recovering the underlying…

Neural and Evolutionary Computing · Computer Science 2026-05-19 Meng Xiang , Pei Yan

Unexpected stimuli induce "error" or "surprise" signals in the brain. The theory of predictive coding promises to explain these observations in terms of Bayesian inference by suggesting that the cortex implements variational inference in a…

Machine Learning · Statistics 2024-10-18 Eli Sennesh , Hao Wu , Tommaso Salvatori

To alleviate the suboptimal performance of belief propagation (BP) decoding of short low-density parity-check (LDPC) codes, a plethora of improved decoding algorithms has been proposed over the last two decades. Many of these methods can be…

Information Theory · Computer Science 2024-11-01 Felix Krieg , Jannis Clausius , Marvin Geiselhart , Stephan ten Brink

In this paper, a new decoding scheme for low-density parity-check (LDPC) codes using the concept of simple product code structure is proposed based on combining two independently received soft-decision data for the same codeword. LDPC codes…

Information Theory · Computer Science 2024-10-30 Beomkyu Shin , Seokbeom Hong , Hosung Park , Jong-Seon No , Dong-Joon Shin

It was recently shown that spatial coupling of individual low-density parity-check codes improves the belief-propagation threshold of the coupled ensemble essentially to the maximum a posteriori threshold of the underlying ensemble. We…

Information Theory · Computer Science 2011-08-03 Vahid Aref , Rüdiger L. Urbanke

In this paper, we model Density Evolution (DE) using Recurrent Neural Networks (RNNs) with the aim of designing capacity-approaching Irregular Low-Density Parity-Check (LDPC) codes for binary erasure channels. In particular, we present a…

Machine Learning · Computer Science 2020-01-07 Eleni Nisioti , Nikolaos Thomos

The complexity-performance trade-off is a fundamental aspect of the design of low-density parity-check (LDPC) codes. In this paper, we consider LDPC codes for the binary erasure channel (BEC), use code rate for performance metric, and…

Information Theory · Computer Science 2016-11-17 Vahid Jamali , Yasser Karimian , Johannes Huber , Mahmoud Ahmadian

We present a new family of low-density parity-check (LDPC) convolutional codes that can be designed using ordered sets of progressive differences. We study their properties and define a subset of codes in this class that have some desirable…

Information Theory · Computer Science 2012-12-21 Marco Baldi , Marco Bianchi , Giovanni Cancellieri , Franco Chiaraluce

In this text we develop the formalism of products and powers of linear codes under componentwise multiplication. As an expanded version of the author's talk at AGCT-14, focus is put mostly on basic properties and descriptive statements that…

Information Theory · Computer Science 2014-10-15 Hugues Randriambololona

Variational autoencoders are prominent generative models for modeling discrete data. However, with flexible decoders, they tend to ignore the latent codes. In this paper, we study a VAE model with a deterministic decoder (DD-VAE) for…

Machine Learning · Computer Science 2020-03-05 Daniil Polykovskiy , Dmitry Vetrov

We present the first theoretical framework that connects predictive coding (PC), a biologically inspired local learning rule, with the minimum description length (MDL) principle in deep networks. We prove that layerwise PC performs…

Machine Learning · Computer Science 2025-07-17 Benjamin Prada , Shion Matsumoto , Abdul Malik Zekri , Ankur Mali

We exhaustively explore the reprogrammability capabilities and the intrinsic universality of the Cartesian product $P \times C$ of the space $P$ of all possible computer programs of increasing size and the space $C$ of all possible…

Formal Languages and Automata Theory · Computer Science 2018-02-02 Jürgen Riedel , Hector Zenil

We analyze a new group testing scheme, termed semi-quantitative group testing, which may be viewed as a concatenation of an adder channel and a discrete quantizer. Our focus is on non-uniform quantizers with arbitrary thresholds. For the…

Information Theory · Computer Science 2015-06-26 Amin Emad , Olgica Milenkovic

Most existing works on analyzing the performance of a random ensemble of low-density parity-check (LDPC) codes assume that the degree distributions of the two ends of a randomly selected edge are independent. In the paper, we take one step…

Information Theory · Computer Science 2023-04-20 Hsiao-Wen Yu , Cheng-En Lee , Ruhui Zhang , Cheng-Shang Chang , Duan-Shin Lee

Cooperative optimization is a new way for finding global optima of complicated functions of many variables. It has some important properties not possessed by any conventional optimization methods. It has been successfully applied in solving…

Information Theory · Computer Science 2007-07-13 Xiaofei Huang

In this paper, we propose a data-driven algorithm to design rate- and length-flexible polar codes. While the algorithm is very general, a particularly appealing use case is the design of codes for automorphism ensemble decoding (AED), a…

Information Theory · Computer Science 2025-10-08 Marvin Rübenacke , Andreas Zunker , Felix Krieg , Stephan ten Brink
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