Analysis of 2D Discrete Wavelet Transform Based Signal Denoising Technique in Brillouin Optical Time Domain Analysis Sensors

Dhaka University Journal of Applied Science & Engineering

Title:	Analysis of 2D Discrete Wavelet Transform Based Signal Denoising Technique in Brillouin Optical Time Domain Analysis Sensors
Authors:	Abul Kalam Azad Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka-1000, Bangladesh
DOI:	PDF
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.
References:	C. A. Galindez-Jamioy, and J. M. Lopez-Higuera, 2102, “Brillouin Distributed Fiber Sensors: An Overview and Applications,” J. of Sensors 2012, Article ID 204121, pp 1-17