A New Family of Graph Representation Matrices: Application to Graph and Signal Classification

Most natural matrices that incorporate information about a graph are the adjacency and the Laplacian matrices. These algebraic representations govern the fundamental concepts and tools in graph signal processing even though they reveal information in different ways. Furthermore, in the context of sp...

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Veröffentlicht in:	IEEE signal processing letters 2024, Vol.31, p.2935-2939
Hauptverfasser:	Averty, T., Boudraa, A. O., Dare-Emzivat, D.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adjacency matrix Eigenvalues Eigenvalues and eigenfunctions Filtering Fourier transforms graph representation Graph representations graph signal processing Graph theory Graphical representations Kernel Laplace equations Laplacian matrix Matrix algebra Signal classification Signal processing Social networking (online) spectral graph theory Support vector machines Visualization
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