Abstract: A system and method for real-time detection of anomalies in high-dimensional systems. Various embodiments detect anomalies quickly and accurately to allow adequate time for appropriate countermeasures to be implemented. The sequential and multivariate anomaly detection method scales well to high-dimensional datasets using a nonparametric and semi-supervised approach that trains only on nominal data.

Abstract: Method for determining the relationship between a track-circuit current signal and a railway vehicle location, including sending, by a track circuit, a current signal across a railway track block, measuring the current signal for different railway vehicles running successively on the railway track block, thus obtaining a plurality of railway vehicle move samples, normalizing the railway vehicle move samples, initializing a reference curve, and applying a Weighted Dynamic Time Warping Barycenter Averaging algorithm to calculate a final reference curve representing the relationship between the measured track-circuit current signal and the railway vehicle location on the railway track block.

Abstract: Method for determining the relationship between a track-circuit current signal and a railway vehicle location, including sending, by a track circuit, a current signal across a railway track block, measuring the current signal for different railway vehicles running successively on the railway track block, thus obtaining a plurality of railway vehicle move samples, normalizing the railway vehicle move samples, initializing a reference curve, and applying a Weighted Dynamic Time Warping Barycenter Averaging algorithm to calculate a final reference curve representing the relationship between the measured track-circuit current signal and the railway vehicle location on the railway track block.