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In this paper, we introduce a new practical and general method for solving the main problem of designing the capacity approaching, optimal rate, irregular low-density parity-check (LDPC) code ensemble over binary erasure channel (BEC).…

Information Theory · Computer Science 2016-11-18 H. Tavakoli , M. Ahmadian Attari , M. Reza Peyghami

Bit-flipping (BF) decoding of low-density parity-check codes is of low complexity but gives inferior performance in general. To improve performance and provide new BF decoder options for complexity-performance tradeoffs, we propose new…

Information Theory · Computer Science 2015-09-01 Tofar C. -Y. Chang , Yu T. Su

We consider the problem of calculating the logical error probability for a stabilizer quantum code subject to random Pauli errors. To access the regime of large code distances where logical errors are extremely unlikely we adopt the…

Quantum Physics · Physics 2013-12-19 Sergey Bravyi , Alexander Vargo

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

It is shown that some well-known and some new cyclic codes with orthogonal parity-check equations can be constructed in the finite-field transform domain. It is also shown that, for some binary linear cyclic codes, the performance of the…

Information Theory · Computer Science 2007-07-13 C. Tjhai , M. Tomlinson , R. Horan , M. Ambroze , M. Ahmed

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

Multilingual end-to-end automatic speech recognition models are attractive due to its simplicity in training and deployment. Recent work on large-scale training of such models has shown promising results compared to monolingual models.…

Computation and Language · Computer Science 2022-10-13 Ke Hu , Bo Li , Tara N. Sainath

Sequential hypothesis testing is a desirable decision making strategy in any time sensitive scenario. Compared with fixed sample-size testing, sequential testing is capable of achieving identical probability of error requirements using less…

Machine Learning · Statistics 2017-11-17 Diyan Teng , Emre Ertin

We show that duals of certain low-density parity-check (LDPC) codes, when used in a standard coset coding scheme, provide strong secrecy over the binary erasure wiretap channel (BEWC). This result hinges on a stopping set analysis of…

Information Theory · Computer Science 2010-10-26 Ananda T. Suresh , Arunkumar Subramanian , Andrew Thangaraj , Matthieu Bloch , Steven McLaughlin

In this paper, new techniques are presented to either simplify or improve most existing upper bounds on the maximum-likelihood (ML) decoding performance of the binary linear codes over additive white Gaussian noise (AWGN) channels. Firstly,…

Information Theory · Computer Science 2015-03-19 Xiao Ma , Jia Liu , Baoming Bai

The typical model for measurement noise in quantum error correction is to randomly flip the binary measurement outcome. In experiments, measurements yield much richer information - e.g., continuous current values, discrete photon counts -…

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple short block codes. After ASCII encoding, the sentence is divided into segments, each…

Information Theory · Computer Science 2026-04-30 Jiafu Hao , Chentao Yue , Wanchun Liu , Branka Vucetic , Yonghui Li

Rule based classifiers that use the presence and absence of key sub-strings to make classification decisions have a natural mechanism for quantifying the uncertainty of their precision. For a binary classifier, the key insight is to treat…

Machine Learning · Computer Science 2020-05-20 James Nutaro , Ozgur Ozmen

We analyze Linear Programming (LP) decoding of graphical binary codes operating over soft-output, symmetric and log-concave channels. We show that the error-surface, separating domain of the correct decoding from domain of the erroneous…

Information Theory · Computer Science 2016-11-15 Michael Chertkov , Mikhail Stepanov

his study presents a novel technique to estimate the computational complexity of sequential decoding using the Berry-Esseen theorem. Unlike the theoretical bounds determined by the conventional central limit theorem argument, which often…

Information Theory · Computer Science 2007-08-20 Po-Ning Chen , Yunghsiang S. Han , Carlos R. P. Hartmann , Hong-Bin Wu

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

The article derives some novel independence measures and contrast functions for Blind Source Separation (BSS) application. For the $k^{th}$ order differentiable multivariate functions with equal hyper-volumes (region bounded by…

Machine Learning · Computer Science 2015-04-13 Dharmani Bhaveshkumar C

Distribution of write error rate (WER) of spin-transfer-torque magnetoreistive random access memory (STT MRAM) caused by a distribution of resistance area product and anisotropy constant is theoretically studied. Assuming that WER is much…

Mesoscale and Nanoscale Physics · Physics 2022-11-01 Hiroshi Imamura , Hiroko Arai , Rie Matsumoto

Minimum Bayes Risk (MBR) decoding has been shown to be a powerful alternative to beam search decoding in a variety of text generation tasks. MBR decoding selects a hypothesis from a pool of hypotheses that has the least expected risk under…

Artificial Intelligence · Computer Science 2024-06-13 Yuu Jinnai , Tetsuro Morimura , Ukyo Honda , Kaito Ariu , Kenshi Abe