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The performance of maximum-likelihood (ML) decoded binary linear block codes over the AWGN channel is addressed via the tangential-sphere bound (TSB) and two of its recent improved versions. The paper is focused on the derivation of the…

Information Theory · Computer Science 2007-07-13 M. Twitto , I. Sason

This paper presents a general approach for optimizing the number of symbols in increments (packets of incremental redundancy) in a feedback communication system with a limited number of increments. This approach is based on a tight normal…

Information Theory · Computer Science 2016-02-17 Kasra Vakilinia , Sudarsan V. S. Ranganathan , Dariush Divsalar , Richard D. Wesel

In this letter, we develop an efficient linear programming (LP) decoding algorithm for low-density parity-check (LDPC) codes. We first relax the maximum likelihood (ML) decoding problem to a LP problem by using check-node decomposition.…

Information Theory · Computer Science 2019-01-24 Jing Bai , Yongchao Wang , Francis C. M. Lau

Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of…

Information Theory · Computer Science 2016-11-17 Panu Chaichanavong , Paul H. Siegel

We develop several analytical lower bounds on the capacity of binary insertion and deletion channels by considering independent uniformly distributed (i.u.d.) inputs and computing lower bounds on the mutual information between the input and…

Information Theory · Computer Science 2015-03-17 Mojtaba Rahmati , Tolga M. Duman

The performance of short polar codes under successive cancellation (SC) and SC list (SCL) decoding is analyzed for the case where the decoder messages are coarsely quantized. This setting is of particular interest for applications requiring…

Information Theory · Computer Science 2020-09-14 Joachim Neu , Mustafa Cemil Coşkun , Gianluigi Liva

Data-parallel SGD is the de facto algorithm for distributed optimization, especially for large scale machine learning. Despite its merits, communication bottleneck is one of its persistent issues. Most compression schemes to alleviate this…

Neural and Evolutionary Computing · Computer Science 2024-02-07 Ashok Vardhan Makkuva , Marco Bondaschi , Thijs Vogels , Martin Jaggi , Hyeji Kim , Michael C. Gastpar

We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density parity-check codes is the linear programming decoder. In…

Information Theory · Computer Science 2015-03-19 Shrinivas Kudekar , Jason K. Johnson , Misha Chertkov

The fully connected conditional random field (CRF) with Gaussian pairwise potentials has proven popular and effective for multi-class semantic segmentation. While the energy of a dense CRF can be minimized accurately using a linear…

Computer Vision and Pattern Recognition · Computer Science 2017-02-15 Thalaiyasingam Ajanthan , Alban Desmaison , Rudy Bunel , Mathieu Salzmann , Philip H. S. Torr , M. Pawan Kumar

We consider the problem of erasure/list decoding using certain classes of simplified decoders. Specifically, we assume a class of erasure/list decoders, such that a codeword is in the list if its likelihood is larger than a threshold. This…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav

Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an ideal maximum-distance-separable code on the binary erasure…

Information Theory · Computer Science 2008-04-21 Enrico Paolini , Gianluigi Liva , Michela Varrella , Balazs Matuz , Marco Chiani

Polar code, with explicit construction and recursive structure, is the latest breakthrough in channel coding field for its low-complexity and theoretically capacity-achieving property. Since polar codes can approach the maximum likelihood…

Information Theory · Computer Science 2019-12-19 Fengyi Cheng , Aijun Liu , Jincheng Dai , Kai Niu , Xiaohu Liang

Recent work has generalized several results concerning the well-understood spiked Wigner matrix model of a low-rank signal matrix corrupted by additive i.i.d. Gaussian noise to the inhomogeneous case, where the noise has a variance profile.…

Statistics Theory · Mathematics 2025-10-10 Debsurya De , Dmitriy Kunisky

The color code is remarkable for its ability to perform fault-tolerant logic gates. This motivates the design of practical decoders that minimise the resource cost of color-code quantum computation. Here we propose a decoder for the planar…

Quantum Physics · Physics 2022-01-20 Kaavya Sahay , Benjamin J. Brown

In this paper, we propose an enhanced quasi-maximum likelihood (EQML) decoder for LDPC codes with short block lengths. After the failure of the conventional belief propagation (BP) decoding, the proposed EQML decoder selects unreliable…

Information Theory · Computer Science 2019-01-31 Peng Kang , Yixuan Xie , Lei Yang , Chen Zheng , Jinhong Yuan , Yuejun Wei

Post-processing of the raw bits produced by a true random number generator (TRNG) is always necessary when the entropy per bit is insufficient for security applications. In this paper, we derive a tight bound on the output min-entropy of…

Cryptography and Security · Computer Science 2024-06-25 Miloš Grujić , Ingrid Verbauwhede

We explored decoding methods for the surface code under depolarizing noise by mapping the problem into the Ising model optimization. We consider two kinds of mapping with and without a soft constraint and also various optimization solvers,…

Quantum error correction (QEC) is indispensable for realizing fault-tolerant quantum computation, yet its effectiveness hinges critically on the classical decoding algorithm that interprets noisy syndrome measurements. Among all possible…

Quantum Physics · Physics 2026-05-19 Hanyan Cao , Ge Yan , Yuxuan Du , Feng Pan

Since the classical work of Berlekamp, McEliece and van Tilborg, it is well known that the problem of exact maximum-likelihood (ML) decoding of general linear codes is NP-hard. In this paper, we show that exact ML decoding of a classs of…

Information Theory · Computer Science 2016-11-17 Weiyu Xu , Babak Hassibi

This paper studies the performance of block coding on an additive white Gaussian noise channel under different power limitations at the transmitter. Lower bounds are presented for the minimum error probability of codes satisfying maximal…

Information Theory · Computer Science 2020-08-19 Gonzalo Vazquez-Vilar