Results 21 to 30 of about 32,468 (150)
Graph Neural Network for Traffic Flow Situation Prediction
Jisuanji kexue yu tansuo, 2021 Road network structure integrated traffic flow situation prediction is a highly nonlinear and complexly spatial-temporal dynamic correlation time-series data prediction problem. However, traditional traffic flow situation forecasting methods cannot model
JIANG Shan, DING Zhiming, XU Xinrun, YAN Jin
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SFTGNN: An Efficient Spherical Fourier Transform-Enhanced Graph Neural Network for High-Accuracy Crystal Property Prediction [PDF]
ACS OmegaZhen Jiang, Hua Tian
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Are there approximate fast fourier transforms on graphs? [PDF]
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 Signal processing on graphs is a recent research domain that seeks to extend classical signal processing tools such as the Fourier transform to irregular domains given by a graph. In such a graph setting, a way to rapidly apply the Fourier transform, i.e. a Fast Fourier Transform (FFT), is lacking.
Le Magoarou, Luc, Gribonval, Rémi
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Fast Discrete Fourier Transform Computations Using the Reduced Adder Graph Technique
EURASIP Journal on Advances in Signal Processing, 2007 It has recently been shown that the n-dimensional reduced adder graph (RAG-n) technique is beneficial for many DSP applications such as for FIR and IIR filters, where multipliers can be grouped in multiplier blocks.
Andrew G. Dempster +2 more
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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: 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 $z^{-1}$.
João Domingos, José M. F. Moura
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Graph Fourier transform based on directed Laplacian [PDF]
2016 International Conference on Signal Processing and Communications (SPCOM), 2016 5 ...
Rahul Singh 0002 +2 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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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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