Results 31 to 40 of about 184,713 (273)
Geary’s c and Spectral Graph Theory
Mathematics, 2021 Spatial autocorrelation, of which Geary’s c has traditionally been a popular measure, is fundamental to spatial science. This paper provides a new perspective on Geary’s c.
Hiroshi Yamada
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Graph Fourier transform based on ℓ1 norm variation minimization [PDF]
Applied 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
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Fast Incremental Spectral Clustering in Titanate Application via Graph Fourier Transform
IEEE 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
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A novel fault diagnosis method for power grid based on graph Fourier transform
Frontiers 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
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Graph Laplacian for Image Anomaly Detection [PDF]
, 2020 Reed-Xiaoli detector (RXD) is recognized as the benchmark algorithm for image anomaly detection; however, it presents known limitations, namely the dependence over the image following a multivariate Gaussian model, the estimation and inversion of a high ...
Grangetto, Marco, Verdoja, Francesco
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Graph Fourier transform based on directed Laplacian [PDF]
2016 International Conference on Signal Processing and Communications (SPCOM), 2016 5 ...
Singh, Rahul +2 more
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Graph Fourier Transform: A Stable Approximation
IEEE 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
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ECG Arrhythmia Classification using High Order Spectrum and 2D Graph Fourier Transform
Applied 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
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IET 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
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Journal 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
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