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eess.SP2025
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…
eess.SP2025
MPFSR-Enhanced GNNs: Spectral Graph Neural Networks Enhancement Through Learnable Multiple-Parameter Graph Fractional Fourier Transforms
Manjun Cui, Xiaopeng Cheng, Yangfan He +1
Graph neural networks (GNNs) excel in processing non-Euclidean data, but traditional spectral GNNs rely on static bases and fundamentally lack active spectral regulation. Although…
eess.SP2025
Graph Chirp Signal and Graph Fractional Vertex-Frequency Energy Distribution
Manjun Cui, Zhichao Zhang, Wei Yao
Graph signal processing (GSP) has emerged as a powerful framework for analyzing data on irregular domains. In recent years, many classical techniques in signal processing (SP) have…