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Ioannis Pitas (AUTH)
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This lecture overviews Graph Signal Processing that has many applications in Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Linear 1D convolution. Cyclic 1D convolution. Graph Basics. Graph Matrix Representations. Graph Fourier-like Basis. Graph Signals. Graph Signal Diffusion. Spatial Graph Convolution. Generalizing Convolutions to Graphs. Spectral Graph Convolution. Graph Filtering: Spatial domain, Spectral domain. Spatial – Spectral connection. Graph Signal Sampling. Graph Signals and Stationarity.
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