Robust Spectral Filtering and Anomaly Detection

Jakub Marecek; Tigran Tchrakian

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arXiv · 1808.01181

Robust Spectral Filtering and Anomaly Detection

Jakub Marecek·Tigran Tchrakian

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Abstract

We consider a setting, where the output of a linear dynamical system (LDS) is, with an unknown but fixed probability, replaced by noise. There, we present a robust method for the prediction of the outputs of the LDS and identification of the samples of noise, and prove guarantees on its statistical performance. One application lies in anomaly detection: the samples of noise, unlikely to have been generated by the dynamics, can be flagged to operators of the system for further study.

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Jakub Marecek, Tigran Tchrakian. 2018-08-03. Robust Spectral Filtering and Anomaly Detection. https://arxiv.org/abs/1808.01181

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