Lu, Yue, Wu, Renjie, Mueen, Abdullah, Zuluaga, Maria A., and Keogh, Eamonn. DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams. Retrieved from https://par.nsf.gov/biblio/10418705. Data Mining and Knowledge Discovery 37.2 Web. doi:10.1007/s10618-022-00911-7.

Lu, Yue, Wu, Renjie, Mueen, Abdullah, Zuluaga, Maria A., & Keogh, Eamonn. DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams. Data Mining and Knowledge Discovery, 37 (2). Retrieved from https://par.nsf.gov/biblio/10418705. https://doi.org/10.1007/s10618-022-00911-7

Lu, Yue, Wu, Renjie, Mueen, Abdullah, Zuluaga, Maria A., and Keogh, Eamonn. "DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams". Data Mining and Knowledge Discovery 37 (2). Country unknown/Code not available. https://doi.org/10.1007/s10618-022-00911-7. https://par.nsf.gov/biblio/10418705.

@article{osti_10418705,
place = {Country unknown/Code not available}, title = {DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams}, url = {https://par.nsf.gov/biblio/10418705}, DOI = {10.1007/s10618-022-00911-7}, abstractNote = {}, journal = {Data Mining and Knowledge Discovery}, volume = {37}, number = {2}, author = {Lu, Yue and Wu, Renjie and Mueen, Abdullah and Zuluaga, Maria A. and Keogh, Eamonn}, }