Publication

Shannon Bounds on Lossy Gray-Wyner Networks

Publications associées (27)

Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

The conditional mean is a fundamental and important quantity whose applications include the theories of estimation and rate-distortion. It is also notoriously difficult to work with. This paper establishes novel bounds on the differential entropy of the co ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Spike-Based Sensing and Communication for Highly Energy-Efficient Sensor Edge Nodes

Mihai Adrian Ionescu, Teodor Rosca

Highly energy-efficient wireless sensor nodes are a prerequisite for a sustainable operation of the Internet of things. Therefore, classical approaches for system design based on digital signal processing are not a viable solution, but system design has to ...

IEEE2022

Does powder averaging remove dispersion bias in diffusion MRI diameter estimates within real 3D axonal architectures?

Marco Pizzolato, Tim Bjørn Dyrby

Noninvasive estimation of axon diameter with diffusion MRI holds the potential to investigate the dynamic properties of the brain network and pathology of neurodegenerative diseases. Recent studies use powder averaging to account for complex white matter a ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Propagation of singularities for the stochastic wave equation

Cheuk Yin Lee

We study the existence and propagation of singularities of the solution to a one-dimensional linear stochastic wave equation driven by an additive Gaussian noise that is white in time and colored in space. Our approach is based on a simultaneous law of the ...

ELSEVIER2022

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

A Revisitation of Low-Rate Bounds on the Reliability Function of Discrete Memoryless Channels for List Decoding

Marco Bondaschi

We revise the proof of low-rate upper bounds on the reliability function of discrete memoryless channels for ordinary and list-decoding schemes, in particular Berlekamp and Blinovsky's zero-rate bound, as well as Blahut's bound for low rates. The available ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

The Price of Distributed: Rate Loss in the CEO Problem

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

In the distributed remote (CEO) source coding problem, many separate encoders observe independently noisy copies of an underlying source. The rate loss is the difference between the rate required in this distributed setting and the rate that would be requi ...

2022

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Erixhen Sula

Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

EPFL2021

Differential Entropy of the Conditional Expectation under Gaussian Noise

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

This paper considers an additive Gaussian noise channel with arbitrarily distributed finite variance input signals. It studies the differential entropy of the minimum mean-square error (MMSE) estimator and provides a new lower bound which connects the diff ...

IEEE2021

On the Advantage of Coherent LoRa Detection in the Presence of Interference

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Orion Afisiadis, Joachim Tobias Tapparel, Sitian Li

It has been shown that the coherent detection of long range (LoRa) signals only provides marginal gains of around 0.7 dB on the additive white Gaussian noise (AWGN) channel. However, ALOHA-based massive Internet-of-Things systems, including LoRa, often ope ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022