Results 21 to 30 of about 12,752 (151)
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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Remote Sensing, 2022 Target position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction
Kefei Liao +3 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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A Regularized Graph Neural Network Based on Approximate Fractional Order Gradients
Mathematics, 2022 Graph representation learning is a significant challenge in graph signal processing (GSP). The flourishing development of graph neural networks (GNNs) provides effective representations for GSP.
Zijian Liu +3 more
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GSP = DSP + Boundary Conditions -- The Graph Signal Processing Companion Model
, 2023 The paper presents the graph signal processing (GSP) companion model that naturally replicates the basic tenets of classical signal processing (DSP) for GSP. The companion model shows that GSP can be made equivalent to DSP 'plus' appropriate boundary conditions (bc) - this is shown under broad conditions and holds for arbitrary undirected or directed ...
Shi, John, Moura, Jose M. F.
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Applied Network Science, 2021 Complex networks lend themselves for the modeling of multidimensional data, such as relational and/or temporal data. In particular, when such complex data and their inherent relationships need to be formalized, complex network modeling and its resulting ...
Stefan Bloemheuvel +2 more
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Graph Signal Processing: Overview, Challenges, and Applications [PDF]
Proceedings of the IEEE, 2017 Research in graph signal processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper, we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing, along
Antonio Ortega +4 more
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Neuroscience Informatics, 2022 Imagined Speech (IS) is the imagination of speech without using the tongue or muscles. In recent studies, IS tasks are increasingly investigated for the Brain-Computer Interface (BCI) applications. Electroencephalography (EEG) signals, which record brain
Aref Einizade +4 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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Short-Time Prediction Model for Urban Traffic Flow Based on Joint Spatio-Temporal Learning [PDF]
Jisuanji gongcheng, 2023 A joint spatio-temporal analysis can reflect the changing pattern of a studied object in the spatio-temporal dimension, which is significant for revealing the spatio-temporal interactions and mechanisms of regional processes.With a focus on joint spatio ...
GE Yuran, FU Qiang
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