Results 31 to 40 of about 163,050 (112)
Undirected Graphs: Is the Shift-Enabled Condition Trivial or Necessary?
IEEE Access, 2021 With the growing application of undirected graphs for signal/image processing on graphs and distributed machine learning, we demonstrate that the shift-enabled condition is as necessary for undirected graphs as it is for directed graphs.
Liyan Chen +4 more
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Dynamic Graph Learning: A Structure-Driven Approach
Mathematics, 2021 The purpose of this paper is to infer a dynamic graph as a global (collective) model of time-varying measurements at a set of network nodes. This model captures both pairwise as well as higher order interactions (i.e., more than two nodes) among the ...
Bo Jiang +5 more
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Node-Adaptive Regularization for Graph Signal Reconstruction
IEEE Open Journal of Signal Processing, 2021 A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem.
Maosheng Yang +3 more
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Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network
Sensors, 2023 In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks ...
Dong Wang +4 more
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Improving Event-Based Non-Intrusive Load Monitoring Using Graph Signal Processing
IEEE Access, 2018 Large-scale smart energy metering deployment worldwide and integration of smart meters within the smart grid will enable two-way communication between the consumer and energy network, thus ensuring improved response to demand.
Bochao Zhao +3 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2023 The paper uses the K-graphs learning method to construct weighted, connected, undirected multiple graphs, aiming to reveal intrinsic relationships of speech samples in the inter-frame and intra-frame. To benefit from the learned multiple graphs’ property
Tingting Wang +4 more
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Gradients of connectivity as graph Fourier bases of brain activity
Network Neuroscience, 2021 The application of graph theory to model the complex structure and function of the brain has shed new light on its organization, prompting the emergence of network neuroscience.
Giulia Lioi +4 more
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Speaker verification method based on cross-domain attentive feature fusion
Tongxin xuebao, 2023 Aiming at the problem that the lack of structure information among speech signal sample in the front-end acoustic features of speaker verification system, a speaker verification method based on cross-domain attentive feature fusion was proposed.Firstly ...
Zhen YANG +3 more
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GSD: An R package for graph signal decomposition
SoftwareXGraph signals residing on the vertices of a graph have recently gained prominence in research of various fields, including neural networks, social networks, traffic patterns, and sensors.
Hyeonglae Cho, Hee-Seok Oh, Donghoh Kim
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Graph Signal Smoothness Based Feature Learning of Brain Functional Networks in Schizophrenia
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 In this paper we study the brain functional network of schizophrenic patients based on resting-state fMRI data. Different from the region of interest (ROI)-level brain networks that describe the connectivity between brain regions, this paper constructs a
Xiaoying Song, Li Chai
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