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Stochastic Functional Analysis and Multilevel Vector Field Anomaly Detection. (arXiv:2207.06229v2 [stat.ML] UPDATED)
Oct. 6, 2022, 1:13 a.m. | Julio E Castrillon-Candas, Mark Kon
stat.ML updates on arXiv.org arxiv.org
Massive vector field datasets are common in multi-spectral optical and radar
sensors, among many other emerging areas of application. In this paper we
develop a novel stochastic functional (data) analysis approach for detecting
anomalies based on the covariance structure of nominal stochastic behavior
across a domain. An optimal vector field Karhunen-Loeve expansion is applied to
such random field data. A series of multilevel orthogonal functional subspaces
is constructed from the geometry of the domain, adapted from the KL expansion.
Detection …
analysis anomaly anomaly detection arxiv detection stochastic vector
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