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eess.SP2026
Generalized Linear Graph Representation: A Compact Operator Space for Graph Signal Processing and Graph Neural Networks
Feiyue Zhao, Zhichao Zhang, Yangfan He
Graph Signal Processing (GSP) and Graph Neural Networks (GNNs) rely fundamentally on the matrix representation of the underlying graph topology. This representation defines key ope…
eess.SP2026
A Unified Fractional Spectral Framework for Spatiotemporal Graph Signals: Bi-Fractional Transform and Geodesic Coupling
Mingzhi Wang, Manjun Cui, Feiyue Zhao +2
Graph signal processing extends spectral analysis to data supported on irregular domains. Existing fractional transforms for two-dimensional graph signals, including the two-dimens…
eess.SP2026
FGFRFT: Fast Graph Fractional Fourier Transform via Exact Spectral Splitting and Fourier-Series Approximation
Ziqi Yan, Mingzhi Wang, Sen Shi +4
The graph fractional Fourier transform (GFRFT) for unitary graph Fourier transform (GFT) matrices can be interpreted through the scalar function on the unit circle. Under…