In this work, we review one of the unsupervised clustering methods to provide low-rank parametric embeddings of network activity patterns. Since optical parameters exhibit spatial and temporal locality, this embedding based on time-series correlation coefficients of optical parameters. To this end, we use hierarchical clustering to create dendrogram representation for different network activity patterns or repeating trends.

© 2019 The Author(s)

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