Title: | Analysis of 2D Discrete Wavelet Transform Based Signal Denoising Technique in Brillouin Optical Time Domain Analysis Sensors |
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Keywords: | Distributed fiber optic sensors, Stimulated Brillouin scattering, Discrete wavelet transform, Least-square curve fitting, Lorentzian profile. |
Abstract: |
In this paper, a novel method is presented for anomaly detection in
multivariate data. The proposed method is based on computing
multivariate entropy of input data at multiple scales, via the MMSE
method, a technique recently proposed for the dynamical complexity
analysis of multivariate data. In the proposed methodology, the
anomalous behaviour is assumed to be generated by a constrained system
and thus is easily differentiated from the established normal behaviour,
in accordance with the “complexity loss” hypothesis, traditionally used
for physiological systems. Simulations are provided to demonstrate the
effectiveness of the approach on real world data sets in terms of
anomaly detection. |
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