8 papers · 1 filter
Optimal Sampling and Reconstruction of Graph Signals in the Fractional Fourier Domain
Xiaopeng Cheng, Zhichao Zhang, Yangfan He
Graph signal sampling and reconstruction are commonly formulated in the graph Fourier transform (GFT) domain. However, the reconstruction performance may be limited when practical…
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…
Node-Oriented Proactive Spectral Modulation: A Unified Fractional Framework for Graph Signal Denoising
Manjun Cui, Zhichao Zhang, Yangfan He
Graph signal denoising is a fundamental task in graph signal processing. While the node-oriented filtering approach enhances spatial adaptability, it suffers from spectral rigidity…
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…
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…
Dynamic Multiple-Parameter Joint Time-Vertex Fractional Fourier Transform and its Intelligent Filtering Methods
Manjun Cui, Ziqi Yan, Yangfan He +1
Dynamic graph signal processing provides a principled framework for analyzing time-varying data defined on irregular graph domains. However, existing joint time-vertex transforms s…