Applications of Double-Wayland Algorithm to Detect Anomalous Signals

The Wayland algorithm has been improved in order to evaluate the degree of visible determinism for dynamics that generate a time series in a simple and accurate manner. Additionally, the Double-Wayland algorithm that we proposed can detect phase transitions among multi-states and non-stationarity in the dynamics. We are applying the Double-Wayland algorithm to detect anomalous signals in railways, stock prices, stabilometry and electrograms recorded by using mapping catheters. In this study, we reported the manner in which these anomalous signals can be detected; however, due to space limitations, we have not reported this data for applications in the field of medicine.