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Santoso, S., Powers, E., Grady, W.M. and Parsons, A.C. (2000) Power Quality Disturbance Waveform Recognition Using Wavelet-Based Neural Classifier—Part 1: Theoretical Foundation. IEEE Transactions on Power Delivery, 15, 222-228.
https://doi.org/10.1109/61.847255

has been cited by the following article:

• TITLE: Wavelets and Entropy for Power Quality Assessment

  AUTHORS: Eduardo Antonio Cano-Plata, Armando J. Ustariz-Farfán, Jorge H. Estrada-Estrada

  KEYWORDS: Wavelets, Entropy, Reflexibility, Regularity, Multiresolution, Multiscale

  JOURNAL NAME: American Journal of Computational Mathematics, Vol.7 No.3, August 21, 2017

  ABSTRACT: In this paper, wavelet transform and entropy are evaluated using the mathematical analysis concepts of reflexibility, regularity and series obtention, these concepts remark the reason to make a selective reference framework for power quality applications. With this idea the paper used the same treatment for the two algorithms (Multiresolution and Multiscale Entropy). The wavelet is denoted to have the most power full consistence to the light off the reflexibility, regularity and series obtention. The paper proposes a power quality technique namely MpqAT.