Results 11 to 20 of about 5,220,012 (288)
Graph Signal Processing: Vertex Multiplication [PDF]
IEEE Signal Processing Letters, 2021 9 pages, 2 ...
Bünyamin Kartal +2 more
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Grid-Graph Signal Processing (Grid-GSP): A Graph Signal Processing Framework for the Power Grid [PDF]
IEEE Transactions on Signal Processing, 2021 The underlying theme of this paper is to explore the various facets of power systems data through the lens of graph signal processing (GSP), laying down the foundations of the Grid-GSP framework. Grid-GSP provides an interpretation for the spatio-temporal properties of voltage phasor measurements, by showing how the well-known power systems modeling ...
Raksha Ramakrishna, Anna Scaglione
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Correlation-Based Graph Smoothness Measures In Graph Signal Processing
2023 31st European Signal Processing Conference (EUSIPCO), 2023 Publisher Copyright: © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.
Vorobyov, Sergiy A. +4 more
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Tropical graph signal processing [PDF]
2017 51st Asilomar Conference on Signals, Systems, and Computers, 2017 For the past few years, the domain of graph signal processing has extended classical Fourier analysis to domains described by graphs. Most of the results were obtained by analogy with the study of heat propagation. We propose to perform a similar analysis in the context of tropical algebra, widely used in theoretical computer science to monitor ...
Gripon, Vincent
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Multi-Kernel Regression for Graph Signal Processing [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 We develop a multi-kernel based regression method for graph signal processing where the target signal is assumed to be smooth over a graph. In multi-kernel regression, an effective kernel function is expressed as a linear combination of many basis kernel functions.
Arun Venkitaraman +2 more
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Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals [PDF]
IEEE Signal Processing Magazine, 2020 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 graph properties and measuring graph signal smoothness.
Miljan Petrovic +3 more
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Graph Signal Processing in the Presence of Topology Uncertainties
IEEE Transactions on Signal Processing, 2020 The goal of this paper is to expand graph signal processing tools to deal with cases where the graph topology is not perfectly known. Assuming that the uncertainty affects only a limited number of edges, we make use of small perturbation analysis to derive closed form expressions instrumental to formulate signal processing algorithms that are ...
Ceci, Elena, Barbarossa, Sergio
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Turning Digital Signal Processing into Graph Signal Processing: Overview and Applications
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 2020 Digital signal processing on graphs (DSP G ) exploits signals whose domain, represented by a graph, is irregular. In this article, we present an overview and some applications of a graph. We also present some approaches used to process data in graphs, highlighting the application of Fourier transform, frequency analysis, filtering, sampling and data ...
Pierre V. Dantas +2 more
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Signal Processing with a Distribution of Graph Operators [PDF]
2021 IEEE Statistical Signal Processing Workshop (SSP), 2021 In this paper, we develop a signal processing framework of a network without explicit knowledge of the network topology. Instead, we make use of knowledge on the distribution of operators on the network. This makes the framework flexible and useful when accurate knowledge of graph topology is unavailable.
Feng Ji, Wee Peng Tay
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Pavement Distress Estimation via Signal on Graph Processing
Sensors, 2022 A comprehensive representation of the road pavement state of health is of great interest. In recent years, automated data collection and processing technology has been used for pavement inspection. In this paper, a new signal on graph (SoG) model of road
Salvatore Bruno +4 more
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