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In many practical communication systems, one binary encoder/decoder pair is used to communicate over a set of parallel channels. Examples of this setup include multi-carrier transmission, rate-compatible puncturing of turbo-like codes, and…

Information Theory · Computer Science 2024-01-25 Christian Häger , Alexandre Graell i Amat , Alex Alvarado , Fredrik Brännström , Erik Agrell

Assuming iterative decoding for binary erasure channels (BECs), a novel tree-based technique for upper bounding the bit error rates (BERs) of arbitrary, finite low-density parity-check (LDPC) codes is provided and the resulting bound can be…

Information Theory · Computer Science 2007-07-13 Chih-Chun Wang , Sanjeev R. Kulkarni , H. Vincent Poor

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

We consider the effect of LLR saturation on belief propagation decoding of low-density parity-check codes. Saturation occurs universally in practice and is known to have a significant effect on error floor performance. Our focus is on…

Information Theory · Computer Science 2014-03-17 Shrinivas Kudekar , Tom Richardson , Aravind Iyengar

Raptor codes are known as precoded rateless codes that achieve the capacity of BEC. However the maximum degree of Raptor codes needs to be unbounded to achieve the capacity. In this paper, we prove that spatially-coupled precoded rateless…

Information Theory · Computer Science 2014-01-29 Kosuke Sakata , Kenta Kasai , Kohichi Sakaniwa

Spatially coupled low-density parity-check (SC-LDPC) codes can achieve the channel capacity under low-complexity belief propagation (BP) decoding, however, there is a non-negligible rate-loss because of termination effects for practical…

Information Theory · Computer Science 2015-12-16 Sebastian Cammerer , Vahid Aref , Laurent Schmalen , Stephan ten Brink

We study classifiers operating under severe classification time constraints, corresponding to 1-1000 CPU microseconds, using Convolutional Tables Ensemble (CTE), an inherently fast architecture for object category recognition. The…

Computer Vision and Pattern Recognition · Computer Science 2016-02-16 Aharon Bar-Hillel , Eyal Krupka , Noam Bloom

This paper introduces a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes, this…

Information Theory · Computer Science 2015-06-16 Santhosh Kumar , Henry D. Pfister

We derive a new fast convergent Density Evolution algorithm for finding optimal rate Low-Density Parity-Check (LDPC) codes used over the binary erasure channel (BEC). The fast convergence property comes from the modified Density Evolution…

Information Theory · Computer Science 2014-09-18 Hassan Tavakoli

Looped Transformers provide advantages in parameter efficiency, computational capabilities, and generalization for reasoning tasks. However, their expressive power regarding function approximation remains underexplored. In this paper, we…

Machine Learning · Computer Science 2025-06-06 Kevin Xu , Issei Sato

This paper introduces a simple but highly efficient ensemble for robust texture classification, which can effectively deal with translation, scale and changes of significant viewpoint problems. The proposed method first inherits the spirit…

Computer Vision and Pattern Recognition · Computer Science 2012-03-06 Shu Kong , Donghui Wang

Consider communication over a binary-input memoryless output-symmetric channel with low density parity check (LDPC) codes and maximum a posteriori (MAP) decoding. The replica method of spin glass theory allows to conjecture an analytic…

Information Theory · Computer Science 2016-11-17 Shrinivas Kudekar , Nicolas Macris

Why do brains and deep networks converge on similar representations? Task-optimized artificial neural networks quantitatively predict primate ventral stream responses despite radically different substrates and optimization dynamics. This…

Artificial Intelligence · Computer Science 2026-03-03 Christian Dittrich , Jennifer Flygare Kinne

A spatially "Mt. Fuji" coupled low-density parity check (LDPC) ensemble is a modified version of the original spatially coupled (SC) LDPC ensemble. Its desirable properties are first observed in experimentally. The decoding error…

Information Theory · Computer Science 2019-08-20 Yuta Nakahara , Toshiyasu Matsushima

The success of deep convolutional neural network (CNN) in computer vision especially image classification problems requests a new information theory for function of image, instead of image itself. In this article, after establishing a deep…

Machine Learning · Computer Science 2017-10-17 Ya-Hui Zhang

Convolution blocks serve as local feature extractors and are the key to success of the neural networks. To make local semantic feature embedding rather explicit, we reformulate convolution blocks as feature selection according to the best…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Ada Gorgun , Yeti Z. Gurbuz , A. Aydin Alatan

It is known that windowed decoding (WD) can effectively balance the performance and complexity of spatially coupled low-density parity-check (LDPC) codes. In this study, we show that information can propagate in a wave-like manner at a…

Information Theory · Computer Science 2025-07-10 Qingqing Peng , Dongxu Chang , Guanghui Wang , Guiying Yan

The investigation of spatio-temporal couplings (STCs) of broadband light beams is becoming a key topic for the optimization as well as applications of ultrashort laser systems. This calls for accurate measurements of STCs. Yet, it is only…

The use of regional coverage satellite constellations is on the rise, urging the need for an optimal constellation design method for complex regional coverage. Traditional constellations are often designed for continuous global coverage,…

Optimization and Control · Mathematics 2020-11-30 Hang Woon Lee , Seiichi Shimizu , Shoji Yoshikawa , Koki Ho

Deep convolutional neural networks, assisted by architectural design strategies, make extensive use of data augmentation techniques and layers with a high number of feature maps to embed object transformations. That is highly inefficient…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Vittorio Mazzia , Francesco Salvetti , Marcello Chiaberge