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A continuous-time white Gaussian channel can be formulated using a white Gaussian noise, and a conventional way for examining such a channel is the sampling approach based on the Shannon-Nyquist sampling theorem, where the original…

Information Theory · Computer Science 2018-10-18 Xianming Liu , Guangyue Han

The capacity of time-varying channels with periodic feedback at the transmitter is evaluated. It is assumed that the channel state information is perfectly known at the receiver and is fed back to the transmitter at the regular…

Information Theory · Computer Science 2007-07-13 Mehdi Ansari Sadrabadi , Mohammad Ali Maddah-Ali , Amir K. Khandani

Denoising diffusion models enable conditional generation and density modeling of complex relationships like images and text. However, the nature of the learned relationships is opaque making it difficult to understand precisely what…

Machine Learning · Computer Science 2024-05-21 Xianghao Kong , Ollie Liu , Han Li , Dani Yogatama , Greg Ver Steeg

We investigate the information distribution among different entities in the weak measurements protocol. Focusing on multilevel, decaying systems under continuous (no-click) monitoring, we derive exact, conservation-type information…

Quantum Physics · Physics 2026-01-30 Yusef Maleki , Luis D. Zambrano Palma , M. Suhail Zubairy

It is known by the experience gained from the gravitational wave detector proto-types that the interferometric output signal will be corrupted by a significant amount of non-Gaussian noise, large part of it being essentially composed of…

General Relativity and Quantum Cosmology · Physics 2009-10-31 E. Chassande-Mottin , S. V. Dhurandhar

Deep learning has emerged as a promising solution for efficient channel state information (CSI) feedback in frequency division duplex (FDD) massive MIMO systems. Conventional deep learning-based methods typically rely on a deep autoencoder…

Signal Processing · Electrical Eng. & Systems 2025-07-29 Haotian Tian , Lixiang Lian , Jiaqi Cao , Sijie Ji

We consider the problem of system identification of partially observed linear time-invariant (LTI) systems. Given input-output data, we provide non-asymptotic guarantees for identifying the system parameters under general heavy-tailed noise…

Systems and Control · Electrical Eng. & Systems 2025-04-28 Vinay Kanakeri , Aritra Mitra

Generative modeling aims to transform random noise into structured outputs. In this work, we enhance video diffusion models by allowing motion control via structured latent noise sampling. This is achieved by just a change in data: we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Ryan Burgert , Yuancheng Xu , Wenqi Xian , Oliver Pilarski , Pascal Clausen , Mingming He , Li Ma , Yitong Deng , Lingxiao Li , Mohsen Mousavi , Michael Ryoo , Paul Debevec , Ning Yu

In this paper, we consider some long-standing problems in communication systems with access to noisy feedback. We introduce a new notion, the residual directed information, to capture the effective information flow (i.e. mutual information…

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

In non-destructive imaging the information about the spatial pattern of a samples interior has to be transferred to the sample surface by certain waves, e.g. ultrasound or electromagnetic waves. At the sample surface these waves can be…

Statistical Mechanics · Physics 2015-04-07 Peter Burgholzer

Deterministic identification (DI) is addressed for Gaussian channels with fast and slow fading, where channel side information is available at the decoder. In particular, it is established that the number of messages scales as…

Information Theory · Computer Science 2021-10-12 Mohammad J. Salariseddigh , Uzi Pereg , Holger Boche , Christian Deppe

Given the recent surge of interest in data-driven control, this paper proposes a two-step method to study robust data-driven control for a parameter-unknown linear time-invariant (LTI) system that is affected by energy-bounded noises.…

Systems and Control · Electrical Eng. & Systems 2022-03-15 Jiabao He , Xuan Zhang , Feng Xu , Junbo Tan , Xueqian Wang

In this paper, we study Sibson's $\alpha$-mutual information in the context of the additive Gaussian noise channel. While the classical case $\alpha = 1$ is well understood and admits deep connections to estimation-theoretic quantities,…

Information Theory · Computer Science 2026-04-14 Mohammad Milanian , Alex Dytso , Martina Cardone

Despite extensive research conducted in the field of image denoising, many algorithms still heavily depend on supervised learning and their effectiveness primarily relies on the quality and diversity of training data. It is widely assumed…

Image and Video Processing · Electrical Eng. & Systems 2023-09-22 Alexandra Malyugina , Nantheera Anantrasirichai , David Bull

Few existing image defogging or dehazing methods consider dense and non-uniform particle distributions, which usually happen in smoke, dust and fog. Dealing with these dense and/or non-uniform distributions can be intractable, since fog's…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Yeying Jin , Wending Yan , Wenhan Yang , Robby T. Tan

Quantum states naturally decay under noise. Many earlier works have quantified and demonstrated lower bounds on the decay rate, showing exponential decay in a wide variety of contexts. Here we study the converse question: are there uniform…

Quantum Physics · Physics 2024-01-01 Nicholas Laracuente , Graeme Smith

Delay constrained linear transmission (LT) strategies are considered for the transmission of composite Gaussian measurements over an additive white Gaussian noise fading channel under an average power constraint. If the channel state…

Information Theory · Computer Science 2016-11-15 Onur Tan , Deniz Gunduz , Jesus Gomez Vilardebo

Deep learning methods have recently been used to construct non-linear codes for the additive white Gaussian noise (AWGN) channel with feedback. However, there is limited understanding of how these black-box-like codes with many learned…

Information Theory · Computer Science 2024-06-06 Yingyao Zhou , Natasha Devroye , Gyorgy Turan , Milos Zefran

We study the problem of communication over an additive white Gaussian noise (AWGN) channel with an AWGN feedback channel. When the feedback channel is noiseless, the classic Schalkwijk-Kailath (S-K) scheme is known to achieve capacity in a…

Information Theory · Computer Science 2017-01-04 Assaf Ben-Yishai , Ofer Shayevitz

Security and privacy are major concerns in modern communication networks. In recent years, the information theory of covert communications, where the very presence of the communication is undetectable to a watchful and determined adversary,…

Information Theory · Computer Science 2017-11-29 Ramin Soltani , Dennis Goeckel , Don Towsley , Amir Houmansadr