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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
JFRFFNet: A Data-Model Co-Driven Graph Signal Denoising Model with Partial Prior Information
Ziqi Yan, Zhichao Zhang
Wiener filtering in the joint time-vertex fractional Fourier transform (JFRFT) domain has shown high effectiveness in denoising time-varying graph signals. Traditional filtering mo…
eess.SP2025
Trainable Joint Time-Vertex Fractional Fourier Transform
Ziqi Yan, Zhichao Zhang
To address limitations of the graph fractional Fourier transform (GFRFT) Wiener filtering and the traditional joint time-vertex fractional Fourier transform (JFRFT) Wiener filterin…