一、报告题目：Graph Fourier Transform for Directed Graphs

二、报告人：孙颀彧 教授

三、时间：2025年6月18日周三

四、地   点：闻理园A4-309

报告摘要：Graph Fourier transform (GFT) is one of the fundamental tools in graph signal processing to decompose graph signals into different frequency components and effectively represent graph signals with strong correlations using various modes of variation. The GFT on undirected graphs has been well-studied, with a conventional approach based on the eigen decomposition of the graph Laplacian. However, this method does not apply to directed graph settings. Several approaches have been proposed to define GFTs on directed graphs, including Jordan decomposition of the graph Laplacian, eigen decomposition of the magnetic Laplacian, and their variants.

In this webinar, the presenter will primarily discuss GFT based on the singular value decompositions of graph shifts. The proposed GFT efficiently represents datasets on directed graphs with strong correlations, and in the corresponding frequency domain, the band limiting procedure provides a good approximation for smooth signals.

报告人简介：孙颀彧于1990年在中国杭州大学获得数学博士学位。他现任美国佛罗里达州奥兰多市中佛罗里达大学数学教授。其研究方向包括应用与计算调和分析、最优控制理论、数学信号处理和采样理论。他与Nader Motee合作，因对空间分布系统理论的基础性贡献，荣获2019年工业与应用数学学会（SIAM）信号处理、通信与控制分会（SIAG/CST）颁发的最佳SICON论文奖。他同时担任《傅里叶分析及其应用杂志》《信号处理前沿》《采样理论、信号处理与数据分析》等多家期刊的编委。

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