Results 21 to 30 of about 184,341 (273)

Graph Fourier transform based on ℓ1 norm variation minimization [PDF]

open access: yesApplied and Computational Harmonic Analysis, 2021
The definition of the graph Fourier transform is a fundamental issue in graph signal processing. Conventional graph Fourier transform is defined through the eigenvectors of the graph Laplacian matrix, which minimize the $\ell_2$ norm signal variation. However, the computation of Laplacian eigenvectors is expensive when the graph is large. In this paper,
Yang, Lihua   +3 more
openaire   +2 more sources

A novel fault diagnosis method for power grid based on graph Fourier transform

open access: yesFrontiers in Energy Research, 2023
The fast and robust identification of fault elements is essential for the security and continuous operation of the power grid. The existing methods might be maloperation for bad data disturbance and require strict and exact synchronization.
Xiaojun Liao   +5 more
doaj   +1 more source

Fast Incremental Spectral Clustering in Titanate Application via Graph Fourier Transform

open access: yesIEEE Access, 2020
In numerous applications the rapid increase of data size with time makes classical clustering algorithms too slow because of the high computational cost.
Gao Shu-Juan
doaj   +1 more source

Graph Fourier transform based on directed Laplacian [PDF]

open access: yes2016 International Conference on Signal Processing and Communications (SPCOM), 2016
5 ...
Singh, Rahul   +2 more
openaire   +2 more sources

Graph Fourier Transform: A Stable Approximation

open access: yesIEEE Transactions on Signal Processing, 2020
In Graph Signal Processing (GSP), data dependencies are represented by a graph whose nodes label the data and the edges capture dependencies among nodes. The graph is represented by a weighted adjacency matrix $A$ that, in GSP, generalizes the Discrete Signal Processing (DSP) shift operator $z^{-1}$.
Domingos, Jo��o   +1 more
openaire   +3 more sources

ECG Arrhythmia Classification using High Order Spectrum and 2D Graph Fourier Transform

open access: yesApplied Sciences, 2020
Heart diseases are in the front rank among several kinds of life threats, due to its high incidence and mortality. Regarded as a powerful tool in the diagnosis of the cardiac disorder and arrhythmia detection, analysis of electrocardiogram (ECG) signals ...
Shu Liu   +3 more
doaj   +1 more source

A robust spatio‐temporal prediction approach for wind power generation based on spectral temporal graph neural network

open access: yesIET Renewable Power Generation, 2022
At present, the penetration of wind power generation is increasing remarkably worldwide, and the accurate wind power forecasting (WPF) is essential to ensure the reliability and economy of the power system.
Yuqin He   +4 more
doaj   +1 more source

Random-Walk Laplacian for Frequency Analysis in Periodic Graphs

open access: yesSensors, 2021
This paper presents the benefits of using the random-walk normalized Laplacian matrix as a graph-shift operator and defines the frequencies of a graph by the eigenvalues of this matrix.
Rachid Boukrab, Alba Pagès-Zamora
doaj   +1 more source

An Attention Encoder-Decoder Dual Graph Convolutional Network with Time Series Correlation for Multi-Step Traffic Flow Prediction

open access: yesJournal of Advanced Transportation, 2022
Accurate traffic prediction is a powerful factor of intelligent transportation systems to make assisted decisions. However, existing methods are deficient in modeling long series spatio-temporal characteristics. Due to the complex and nonlinear nature of
Shanchun Zhao, Xu Li
doaj   +1 more source

Solution to the Dirichlet Problem of the Wave Equation on a Star Graph

open access: yesMathematics, 2023
In this paper, the solution to the Dirichlet problem for the wave equation on the star graph is constructed. To begin, we solve the boundary value problem on the interval (on one edge of the graph).
Gaukhar Arepova   +2 more
doaj   +1 more source

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