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Related publications (44)

The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

Piscataway2024

Update on yesterday's dose-Use of delivery log-files for daily adaptive proton therapy (DAPT)

Marco Matter

In daily adaptive proton therapy (DAPT), the treatment plan is re-optimized on a daily basis. It is a straightforward idea to incorporate information from the previous deliveries during the optimization to refine this daily proton delivery. A feedback sign ...

2020

Graph Transform Optimization With Application to Image Compression

Pascal Frossard, Giulia Fracastoro

In this paper, we propose a new graph-based transform and illustrate its potential application to signal compression. Our approach relies on the careful design of a graph that optimizes the overall rate-distortion performance through an effective graph-bas ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Localized Spectral Graph Filter Frames: A Unifying Framework, Survey of Design Considerations, and Numerical Comparison

David Shuman

A major line of work in graph signal processing [2] during the past 10 years has been to design new transform methods that account for the underlying graph structure to identify and exploit structure in data residing on a connected, weighted, undirected gr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Slepian Guided Filtering of Graph Signals

Dimitri Nestor Alice Van De Ville, Miljan Petrovic

Joint localization of graph signals in vertex and spectral domain is achieved in Slepian vectors calculated by either maximizing energy concentration (mu) or minimizing modified embedded distance (xi) in the subgraph of interest. On the other hand, graph L ...

SPIE-INT SOC OPTICAL ENGINEERING2019

Experimental Validation of an Explicit Power-Flow Primary Control in Microgrids

Jean-Yves Le Boudec, Mario Paolone, Lorenzo Enrique Reyes Chamorro, Enrica Scolari, Andrey Bernstein, Andreas Martin Kettner, Niek Johannes Bouman, Benoit Jacques Louis Marie Cathiard

The existing approaches to control electrical grids combine frequency and voltage controls at different time-scales. When applied in microgrids with stochastic distributed-generation, grid quality of service problems may occur, such as under- or overvoltag ...

2018

Global and Local Uncertainty Principles for Signals on Graphs

Pierre Vandergheynst, Nathanaël Perraudin, Benjamin Ricaud, David Shuman

Uncertainty principles such as Heisenberg's provide limits on the time-frequency concentration of a signal, and constitute an important theoretical tool for designing and evaluating linear signal transforms. Generalizations of such principles to the graph ...

2018

Robust control of constrained systems given an information structure

Maryam Kamgarpour, Luca Furieri

We study finite horizon optimal control where the controller is subject to sensor-information constraints, that is, each input has access to a fixed subset of states at all times. In particular, we consider linear systems affected by exogenous disturbances ...

IEEE2017

Graph-based structures in data science

Nathanaël Perraudin

State-of-the-art data analysis tools have to deal with high-dimensional data. Fortunately, the inherent dimensionality of data is often much smaller, as it has an internal structure limiting its degrees of freedom. In most cases, this structure can be appr ...

EPFL2017

Controlling the Electrical State via Uncertain Power Injections in Three-Phase Distribution Networks

Jean-Yves Le Boudec, Mario Paolone, Cong Wang

We consider the problem of controlling the electrical state of a three-phase distribution network by enforcing the explicit power injection. More precisely, we assume that the power injection is constrained to reside in some uncertainty set, and the proble ...

2017

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