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In this paper, we derive upper bounds on generalization errors for deep neural networks with Markov datasets. These bounds are developed based on Koltchinskii and Panchenko's approach for bounding the generalization error of combined…

Machine Learning · Statistics 2022-10-13 Lan V. Truong

In this paper, the bit error performance of a family of likelihood ascent search (LAS) multiuser detectors is analyzed. An upper bound on the BER of any LAS detector is obtained by bounding the fixed point region with the worst initial…

Information Theory · Computer Science 2016-11-15 Yi Sun

We study the two-user multiple-input single-output (MISO) Gaussian interference channel where the transmitters have perfect channel state information and employ single-stream beamforming. The receivers are capable of performing successive…

Information Theory · Computer Science 2015-06-11 Johannes Lindblom , Eleftherios Karipidis , Erik G. Larsson

This paper presents a novel three-dimensional (3D) 8-ary noise modulation scheme that introduces a new dimension: the mixture probability of a Mixture of Gaussian (MoG) distribution. This proposed approach utilizes the dimensions of mean…

Signal Processing · Electrical Eng. & Systems 2025-10-03 Hadi Zayyani , Felipe A. P. de Figueiredo , Mohammad Salman , Rausley A. A. de Souza

Recently, Samorodnitsky proved a strengthened version of Mrs. Gerber's Lemma, where the output entropy of a binary symmetric channel is bounded in terms of the average entropy of the input projected on a random subset of coordinates. Here,…

Information Theory · Computer Science 2016-05-11 Or Ordentlich

High-throughput optical communication systems utilize binary soft-decision forward error correction (SD-FEC) with bit interleaving over the bit channels. The generalized mutual information (GMI) is an achievable information rate (AIR) in…

Information Theory · Computer Science 2024-01-30 Tsuyoshi Yoshida , Magnus Karlsson , Erik Agrell

A new lower bound on the error probability of maximum likelihood decoding of a binary code on a binary symmetric channel was proved in Barg and McGregor (2004, cs.IT/0407011). It was observed in that paper that this bound leads to a new…

Information Theory · Computer Science 2007-07-13 Alexander Barg

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the…

Information Theory · Computer Science 2020-10-16 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

There are rising scenarios in communication systems, where the noises exhibit impulsive behavior and are not adequate to be modeled as the Gaussian distribution. The generalized Gaussian distribution instead is an effective model to…

Information Theory · Computer Science 2022-05-12 Jinzhe Pan , Wai Ho Mow

Variable-length block-coding schemes are investigated for discrete memoryless channels with ideal feedback under cost constraints. Upper and lower bounds are found for the minimum achievable probability of decoding error $P_{e,\min}$ as a…

Information Theory · Computer Science 2020-01-03 B. Nakiboglu , R. G. Gallager

This paper proposes a belief propagation (BP)-based algorithm for sequential detection and estimation of multipath component (MPC) parameters based on radio signals. Under dynamic channel conditions with moving transmitter/receiver, the…

Information Theory · Computer Science 2022-05-24 Xuhong Li , Erik Leitinger , Alexander Venus , Fredrik Tufvesson

The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid…

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

This work studies an information-theoretic performance limit of an integrated sensing and communication (ISAC) system where the goal of sensing is to estimate a random continuous state. Considering the mean-squared error (MSE) for…

Information Theory · Computer Science 2025-01-30 Daewon Seo

This paper presents new structure and adaptation criterion for equalization of two-dimensional magnetic recording channels, as opposed to typical linear equalizer with minimum mean square error (MMSE) as adaptation criterion. To compensate…

Signal Processing · Electrical Eng. & Systems 2019-12-18 Jinlu Shen , Nitin Nangare

This paper considers the problem of code design for a channel where communications and radar systems coexist, modeled as having both Additive White Gaussian Noise (AWGN) and Additive Radar Interference (ARI). The issue of how to adapt or…

Information Theory · Computer Science 2019-04-12 Federico Brunero , Daniela Tuninetti , Natasha Devroye

Searching for gravitational-wave signals is a challenging and computationally intensive endeavor undertaken by multiple independent analysis pipelines. While detection depends only on observed noisy data, it is sometimes inconsistently…

General Relativity and Quantum Cosmology · Physics 2024-03-15 Matthew Mould , Christopher J. Moore , Davide Gerosa

A new approach for blind channel equalization and decoding, variational inference, and variational autoencoders (VAEs) in particular, is introduced. We first consider the reconstruction of uncoded data symbols transmitted over a noisy…

Machine Learning · Computer Science 2020-04-14 Avi Caciularu , David Burshtein

Integrated sensing and communication is regarded as a key enabler for next-generation wireless networks. To optimize the transmitted waveform for both sensing and communication, various performance metrics must be considered. This work…

We study the two-user broadcast channel with degraded message sets and derive second-order achievability rate regions. Specifically, the channel noises are not necessarily Gaussian and we use spherical codebooks for both users. The weak…

Information Theory · Computer Science 2024-10-24 Zhuangfei Wu , Lin Bai , Jinpeng Xu , Lin Zhou , Mehul Motani

A two-terminal distributed binary hypothesis testing problem over a noisy channel is studied. The two terminals, called the observer and the decision maker, each has access to $n$ independent and identically distributed samples, denoted by…

Other Statistics · Statistics 2023-02-07 Sreejith Sreekumar , Deniz Gündüz