Dataset: 97.mat

100.mat

bearing_time_series.mat

Dataset: A 60-second snippet of an ECG.mat (data source: https://archive.physionet.org/cgi-bin/atm/ATM)

Dataset: 4.csv

Dataset: MIT-BIH Long-Term ECG Database14157m.mat

Dataset: lookaheads.mat

Code: test_lookaheads_of_diff_len.m

plot_lookaheads.m

Dataset: link (CAISO_zone_4_.csv)

Dataset: castironToSteel_36760.mat

Dataset: RandomWalk2.mat

Dataset: 100_highest_discord_values_for_anomaly_case.txt

100_highest_discord_values_for_NO_anomaly_case.txt

Code: plot.m

Dataset: ECG.mat

time_taken_BruteForce.mat

time_taken_BruteForceMASSNotPower.mat

time_taken_BruteForceMASSPowerOf2.mat

time_taken_SCRIMP.mat

time_taken_DAMPTrueOnline.mat

time_taken_DAMPEffectivelyOnline.mat

Code: baselines_code.zip

plot_baselines.m

Dataset: ECG.mat

Boniol, P., et. al. Unsupervised and scalable subsequence anomaly detection in large data series. The VLDB Journal. 1-23.

Dataset: log_demo.txt

Code: demo_DAMP.m

Dataset: oneElectricityLoadDiagram.mat

Code: test_DAMP_confusionmatrix.m (Random seeds are given in the code)

Dataset: MG.txt

Code: DAMP_trillion.m (Random seeds are given in the code)