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Median based algorithm as an entropy function for noise detectionin wavelet trees for data reconciliation

Research output: Contributions to collected editions/works › Chapter › peer-review

Authors

The noise detection and the data cleaning find application in data com-pressions for images and voice as well as in their analysis and recognition,datatransmission,datareconciliation,fault detection and in general in all application area of the signal processing and measurements.The content of this paper can offer the possibility to improve the state of the art of all those procedures with denoising methods which use a thresholding tech-nique implying a free thresholding one,running in wavelet packets.The author presents a technique which deals with a free thresholding method related to the on-line peak noise variance estimation even for signals with a small S/N ratio.The se cond innovative aspect consists of use of wavelet packets which give more elasticity to the technique.The basic idea is to characterize the noise like an in coherent part of the measure dsignal.It is performed through the wavelet tree by choosing the subspaces where the median value of the wavelet components has minimum.In this sense the proposed median based algorithm can be seen a s an entropy function and this analogyis shown.The paper provides to show general properties of the wavelet packet son which the proposed procedure is based.The developed algorithmis to tally general even though it is applied by using Haar wavelet packets and it is present in some industrial software plat-forms to detect sensor out liers because of their easy structure. More,it is currently integrated in the inferential modeling platform of the Advanced Control and Simulation Solution Responsible Unit with in ABB's(Asea Brown Boveri)industry division.

Original languageEnglish
Title of host publicationNew Developments in Mathematics Research
EditorsNatalie L Clarke, Alex P Ronson
Number of pages20
PublisherNova Science Publishers, Inc.
Publication date2011
Pages85-104
ISBN (print)9781613242520
Publication statusPublished - 2011
Externally publishedYes

    Research areas

  • Data reconciliation, Fault detection, Haar functions, Noise detection, Signal processing, Variance, Wavelets, Wavelets'packets
  • Engineering

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