Artificial Intelligence

   

Graph Signal Processing: Towards the Diffused Spectral Clustering

Authors: Reda ALAMI

Graph signal processing is an emerging field of research. When the structure of signalscanberepresentedasagraph,itallowstofullyexploittheirinherentstructure. It has been shown that the normalized graph Laplacian matrix plays a major role in the characterization of a signal on a graph. Moreover, this matrix plays a major role in clustering large data set. In this paper, we present the diffused spectral clustering: a novel handwritten digits clustering algorithm based on the normalizedgraphLaplacianproperties. It’saclevercombinationbetweenagraph feature space transformation and the spectral clustering algorithm. Experimentally, our proposal outperforms the other algorithms of the state-of-art.

Comments: 5 Pages.

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Submission history

[v1] 2019-06-14 22:47:13

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