BeatLex is an algorithm that succintly summarizes and forecasts time series data. It is designed for data containing patterns that occur repeatedly, especially if these patterns are complex and nonlinear, change over time, and may distortions in their shape or length.
BeatLex has the following properties:


The source code and experiments used in the paper are available: [Download]


The MITDB dataset used in the paper can be found at PhysioNet https://physionet.org/cgi-bin/atm/ATM?database=mitdb.

The MOCAP data can be found at http://mocap.cs.cmu.edu. The preprocessed time series as used in our paper can be found in our source code package.