Publications associées à Downsampling (signal processing)

Realization and Control of Bulk and Surface Modes in 3D Nanomagnonic Networks by Additive Manufacturing of Ferromagnets

Dirk Grundler, Mohammad Hamdi, Mingran Xu, Huixin Guo, Axel Johan Marie Deenen

The high-density integration in information technology fuels the research on functional 3D nanodevices. Particularly ferromagnets promise multifunctional 3D devices for nonvolatile data storage, high-speed data processing, and non-charge-based logic operat ...

WILEY-V C H VERLAG GMBH2023

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Dimitri Nestor Alice Van De Ville, Maude Schneider, Daniela Maria Zöller, Anjali Bagunu Tarun

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could sign ...

eLIFE SCIENCES PUBL LTD2021

Characterization of Non-Stationary Signals in Electric Grids: a Functional Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

With the expanding role of converter-interfaced distributed energy resources, modern power grids are evolving towards low-inertia networks that are increasingly vulnerable to extreme dynamics. Consequently, advanced signal processing techniques are needed ...

2021

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Jean-Philippe Thiran, Tobias Kober, Tom Hilbert, Reto Meuli

Purpose MP2RAGE T-1-weighted imaging has been shown to be beneficial for various applications, mainly because of its good grey-white matter contrast, its B-1-robustness and ability to derive T(1)maps. Even using parallel imaging, the method requires long a ...

WILEY2020

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Pascal Frossard, Michael Bronstein, Laura Toni, Xiaowen Dong

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics

José Luis Abelleira Fernández, Sofia Moco

aSummary: Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches re ...

OXFORD UNIV PRESS2020

Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Raphaël Pierre Liégeois

The emerging field of graph signal processing (GSP) allows one to transpose classical signal processing operations (e.g., filtering) to signals on graphs. The GSP framework is generally built upon the graph Laplacian, which plays a crucial role in studying ...

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

Dynamics Of Brain Activity Captured By Graph Signal Processing Of Neuroimaging Data To Predict Human Behaviour

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton

Joint structural and functional modelling of the brain based on multimodal imaging increasingly show potential in elucidating the underpinnings of human cognition. In the graph signal processing (GSP) approach for neuroimaging, brain activity patterns are ...

IEEE2020

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Downsampling (signal processing)

Realization and Control of Bulk and Surface Modes in 3D Nanomagnonic Networks by Additive Manufacturing of Ferromagnets

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Characterization of Non-Stationary Signals in Electric Grids: a Functional Dictionary Approach

A Graph Signal Processing Framework for the Classification of Temporal Brain Data

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Graph Signal Processing for Machine Learning: A Review and New Perspectives

AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics

Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals

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

Dynamics Of Brain Activity Captured By Graph Signal Processing Of Neuroimaging Data To Predict Human Behaviour

Graph Chatbot

Chattez avec Graph Search

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Dynamics Of Brain Activity Captured By Graph Signal Processing Of Neuroimaging Data To Predict Human Behaviour

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

A Graph Signal Processing Framework for the Classification of Temporal Brain Data

Characterization of Non-Stationary Signals in Electric Grids: a Functional Dictionary Approach

AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics

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