2019/02/27 by Jiasong Wu, Wu, Jiasong, Fuzhi Wu +13 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Bioinformatics and Genomic Networks #Computational Drug Discovery Methods #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Graph theory and applications
paper · pdf · doi:10.48550/arxiv.1902.10471
openalex publication_date 2019/02/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the key challenges in the area of signal processing on graphs is to design transforms and dictionaries methods to identify and exploit structure in signals on weighted graphs. In this paper, we first generalize graph Fourier transform (GFT) to graph fractional Fourier transform (GFRFT), which is then used to define a novel transform named spectral graph fractional wavelet transform (SGFRWT), which is a generalized and extended version of spectral graph wavelet transform (SGWT). A fast algorithm for SGFRWT is also derived and implemented based on Fourier series approximation. The potential applications of SGFRWT are also presented.