Graph Theory and Economic Models: from Small to Large Size Applications
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2020, Digital Signal Processing: A Review JournalCitation Excerpt :Since the emergence of graph signal processing (GSP), the theory and applications of GSP have been extensively studied [1–12]. Graphs can be used to capture many various phenomena in nature where data and objects are invariably inter-connected such as human brain [2], ecological, financial [13], and social [14] networks. GSP has found a wide range of applications including wavelet/filter bank design [15–18], learning graphs from observed data [19–21], graph signal restoration [22,23], image/point cloud processing [24], and deep learning on graphs [25], to name but a few.
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