Analysis of Time Series Novelty Detection Strategies for Synthetic and Real Data
Novelty detection is inspired by animal behavior and can be applied to a variety of practical situations. By automatically bringing attention to anomalous events, without the need of previously defining those events, it can perform certain tasks that would otherwise require human scrutiny. This paper reviews some approaches to the problem when applied to the time series analysis problem.
time series novelty detection neural networks signal processing principal component analysis reduced coulomb energy networks density probability estimation