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Convolutional sparse coding (CSC) can learn representative shift-invariant patterns from multiple kinds of data. However, existing CSC methods can only model noises from Gaussian distribution, which is restrictive and unrealistic. In this…

Machine Learning · Computer Science 2020-04-22 Yaqing Wang , James T. Kwok , Lionel M. Ni

It is common practice to collect observations of feature and response pairs from different environments. A natural question is how to identify features that have consistent prediction power across environments. The invariant causal…

Information Theory · Computer Science 2022-07-01 Austin Goddard , Yu Xiang , Ilya Soloveychik

The capacity of a network in which a multiple access channel (MAC) generates interference to a single-user channel is studied. An achievable rate region based on superposition coding and joint decoding is established for the discrete case.…

Information Theory · Computer Science 2012-09-06 Fangfang Zhu , Xiaohu Shang , Biao Chen , H. Vincent Poor

In this paper, we investigate the additive Gaussian noise channel with noisy feedback. We consider the setup of linear coding of the feedback information and Gaussian signaling of the message (i.e. Cover-Pombra Scheme). Then, we derive the…

Information Theory · Computer Science 2015-03-19 Chong Li , Nicola Elia

Many communication applications incorporate event-triggered behavior, where the conventional Shannon capacity may not effectively gauge performance. Consequently, we advocate for the concept of identification capacity as a more suitable…

Information Theory · Computer Science 2025-02-04 Ilya Vorobyev , Christian Deppe , Holger Boche

This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any…

Information Theory · Computer Science 2008-01-17 Gesualdo Scutari , Daniel P. Palomar , Sergio Barbarossa

Entropy comparison inequalities are obtained for the differential entropy $h(X+Y)$ of the sum of two independent random vectors $X,Y$, when one is replaced by a Gaussian. For identically distributed random vectors $X,Y$, these are closely…

Information Theory · Computer Science 2024-07-24 Lampros Gavalakis , Ioannis Kontoyiannis , Mokshay Madiman

We extend previous results on covert communication over the additive white Gaussian noise channel to two other types of additive noise channels. The first is the Gaussian channel with memory, where the noise sequence is a Gaussian vector…

Information Theory · Computer Science 2023-03-22 Cécile Bouette , Laura Luzzi , Ligong Wang

If a sender and a receiver lack precise knowledge about the communication line that connects them, designing a scheme to reliably transmit information becomes more challenging. This has been studied in classical and quantum information…

Quantum Physics · Physics 2024-08-27 Paula Belzig

The cognitive interference channel (C-IFC) consists of a classical two-user interference channel in which the message of one user (the "primary" user) is non-causally available at the transmitter of the other user (the "cognitive" user). We…

Information Theory · Computer Science 2016-11-18 Stefano Rini , Daniela Tuninetti , Natasha Devroye

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph

Nonlinear interference is modeled by a time-varying conditionally Gaussian channel. It is shown that approximating this channel with a time-invariant channel imposes considerable loss in the performance of channel decoding. An adaptive…

Information Theory · Computer Science 2021-02-02 Reza Rafie Borujeny , Frank R. Kschischang

We present an algorithm for calculation of the Gaussian classical capacity of a quantum bosonic memory channel with additive Gaussian noise. The algorithm, restricted to Gaussian input states, is applicable to all channels with noise…

Quantum Physics · Physics 2015-03-17 Joachim Schäfer , Evgueni Karpov , Nicolas J. Cerf

The feedback capacity of the stationary Gaussian additive noise channel has been open, except for the case where the noise is white. Here we find the feedback capacity of the stationary first-order moving average additive Gaussian noise…

Information Theory · Computer Science 2007-07-16 Young-Han Kim

Quantum capacity gives the fundamental limit of information transmission through a channel. However, evaluating the quantum capacities of a continuous-variable bosonic quantum channel, as well as finding an optimal code to achieve the…

Quantum Physics · Physics 2025-10-03 Adam Taylor , Michael Hanks , Hyukjoon Kwon , M. S. Kim

We consider the problem of universally communicating over an unknown and arbitrarily varying channel, using feedback. The focus of this paper is on determining the input behavior, and specifically, a prior distribution which is used to…

Information Theory · Computer Science 2012-02-03 Yuval Lomnitz , Meir Feder

Arbitrarily varying channels offer a powerful framework for analyzing the robustness of quantum communication systems, especially for classical-quantum models, where the analysis displays strengths or weaknesses of specific signal…

Quantum Physics · Physics 2025-07-25 Janis Nötzel , Florian Seitz

This paper investigates the asymptotic expansion for the maximum rate of fixed-length codes over a parallel Gaussian channel with feedback under the following setting: A peak power constraint is imposed on every transmitted codeword, and…

Information Theory · Computer Science 2017-07-11 Silas L. Fong , Vincent Y. F. Tan

We investigate how to exploit intermittent feedback for interference management by studying the two-user Gaussian interference channel (IC). We approximately characterize (within a universal constant) the capacity region for the Gaussian IC…

Information Theory · Computer Science 2016-11-17 Can Karakus , I-Hsiang Wang , Suhas Diggavi

We study a lossy source coding problem for an arbitrarily varying remote source (AVRS) which was proposed in a prior work. An AVRS transmits symbols, each generated in an independent and identically distributed manner, which are sought to…

Information Theory · Computer Science 2018-09-13 Amitalok J. Budkuley , Bikash Kumar Dey , Sidharth Jaggi , Vinod M. Prabhakaran