Novelty Detection for Multivariate Data Streams with Prob...
The autonomous detection of unexpected changes in data is called novelty detection. Multivariate data streams consisting of measurements from multiple sensors often form the basis to detect such changes. Specific examples of such changes are, for instance, cardiac arrhythmias, power failures, storms or network attacks. Accordingly, changes can affect both a system itself and the environment in which it is ...