Results 11 to 20 of about 4,335,273 (293)
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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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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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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Protein-Protein Interaction Prediction via Graph Signal Processing
IEEE Access, 2021 This paper tackles the problem of predicting the protein-protein interactions that arise in all living systems. Inference of protein-protein interactions is of paramount importance for understanding fundamental biological phenomena, including cross ...
Stefania Colonnese +4 more
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Signal Processing on Simplicial Complexes With Vertex Signals
IEEE Access, 2022 In classical graph signal processing (GSP), the underlying topological structures are restricted in terms of dimensionality. A graph or a 1-complex is a combinatorial object that models binary relations, which do not directly capture complex high arity ...
Feng Ji, Giacomo Kahn, Wee Peng Tay
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Graph wavelet transform for image texture classification
IET Image Processing, 2021 Graph is a data structure that can represent complex relationships among data. Graph signal processing, unlike traditional signal processing, explicitly considers the structure and relationship among the signal samples.
Yu‐Long Qiao +4 more
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Graph signal processing based underwater image enhancement techniques
Engineering Science and Technology, an International Journal, 2022 This paper presents two new methods based on graph signal processing (GSP) techniques to enhance underwater images. The proposed schemes utilize the graph Fourier transform (GFT) and graph wavelet filterbanks in place of the conventional Fourier and ...
Shobha Sharma, Tarun Varma
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Stationary Signal Processing on Graphs [PDF]
IEEE Transactions on Signal Processing, 2017 Graphs are a central tool in machine learning and information processing as they allow to conveniently capture the structure of complex datasets. In this context, it is of high importance to develop flexible models of signals defined over graphs or networks.
Perraudin, Nathanaël +1 more
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Multilayer graph spectral analysis for hyperspectral images
EURASIP Journal on Advances in Signal Processing, 2022 Hyperspectral imaging has broad applications and impacts in areas including environmental science, weather, and geo/space exploration. The intrinsic spectral–spatial structures and potential multi-level features in different frequency bands make ...
Songyang Zhang, Qinwen Deng, Zhi Ding
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