Détection non supervisée de motifs sur séries temporelles

We present a new algorithm for pattern detection in time series. It uses a graph that quantifies the similarity of pairs of subsequences of a given signal, and topological data analysis tools to detect and reconstruct the patterns from the graph without any information a priori about the number of patterns.