Noise level estimation using haar wavelet packet trees for sensor robust outlier detection

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Noise level estimation using haar wavelet packet trees for sensor robust outlier detection. / Mercorelli, Paolo; Frick, Alexander.
Computational Science and Its Applications – ICCSA 2006: international conference, Glasgow, UK, May 8 - 11, 2006; proceedings. Hrsg. / Marina Gavrilova; Osvaldo Gervasi; Vipin Kumar; C.J. Kenneth Tan; David Taniar; Antonio Laganà; Youngsong Mun; Hyunseung Choo. Band 1 Berlin: Springer, 2006. S. 847-856 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 3980 LNCS).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Mercorelli, P & Frick, A 2006, Noise level estimation using haar wavelet packet trees for sensor robust outlier detection. in M Gavrilova, O Gervasi, V Kumar, CJK Tan, D Taniar, A Laganà, Y Mun & H Choo (Hrsg.), Computational Science and Its Applications – ICCSA 2006: international conference, Glasgow, UK, May 8 - 11, 2006; proceedings. Bd. 1, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 3980 LNCS, Springer, Berlin, S. 847-856, International Conference on Computational Science and Its Applications - ICCSA 2006, Glasgow, Großbritannien / Vereinigtes Königreich, 08.05.06. https://doi.org/10.1007/11751540_92

APA

Mercorelli, P., & Frick, A. (2006). Noise level estimation using haar wavelet packet trees for sensor robust outlier detection. In M. Gavrilova, O. Gervasi, V. Kumar, C. J. K. Tan, D. Taniar, A. Laganà, Y. Mun, & H. Choo (Hrsg.), Computational Science and Its Applications – ICCSA 2006: international conference, Glasgow, UK, May 8 - 11, 2006; proceedings (Band 1, S. 847-856). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 3980 LNCS). Springer. https://doi.org/10.1007/11751540_92

Vancouver

Mercorelli P, Frick A. Noise level estimation using haar wavelet packet trees for sensor robust outlier detection. in Gavrilova M, Gervasi O, Kumar V, Tan CJK, Taniar D, Laganà A, Mun Y, Choo H, Hrsg., Computational Science and Its Applications – ICCSA 2006: international conference, Glasgow, UK, May 8 - 11, 2006; proceedings. Band 1. Berlin: Springer. 2006. S. 847-856. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11751540_92

Bibtex

@inbook{45c4ad451bf74d3680b448c5cb8d5afd,
title = "Noise level estimation using haar wavelet packet trees for sensor robust outlier detection",
abstract = "The paper is related to the on-line noise variance estimation. In practical use, it is important to estimate the noise level from the data rather than to assume that the noise level is known. The paper presented a free thresholding method related to the on-line peak noise variance estimation even for signal with small S/N ratio. The basic idea is to characterize the noise like an incoherent part of the measured signal. This is performed through the wavelet tree by choosing the subspaces where the median value of the wavelet components has minimum. The paper provides to show nice general properties of the wavelet packets on which the proposed procedure is based. The developed algorithm is totally general even though is applied by using Haar wavelet packets and it is present in some industrial software platforms to detect sensor outliers. More, it is currently integrated in the inferential modeling platform of the Advanced Control and Simulation Solution Responsible Unit within ABB{\textquoteright}s industry division.",
keywords = "Engineering, Noise Variance, Wavelet Packet, Minimum Description Length, Thresholding Method, Wavelet Shrinkage",
author = "Paolo Mercorelli and Alexander Frick",
note = "Conference code: 67786 Export Date: 22 May 2012 Source: Scopus doi: 10.1007/11751540_93 Language of Original Document: English Correspondence Address: Cattani, C.; Department of Mechanical Engineering, University of Salerno, Via Ponte Don Melillo-Invariante, 84084 Fisciano, SA, Italy; email: ccattani@unisa.it References: Amphlett, J.C., Baumert, R.M., Mann, R.F., Peppley, B.A., Roberge, P.R., Performance modelling of the ballard mark iv solid polymer electrolyte fuel cell (1995) Journal of Electrochemical Society, 142 (1), pp. 9-15; Cattani, C., Harmonic wavelet solutions of the schr{\"o}dinger equation (2003) International Journal of Fluid Mechanics Research, 5 (1-10), pp. 1064-2277. , ISNN; Cattani, C., Harmonic wavelets towards solution of nonlinear pde (2003) Computers and Mathematics with Applications, 50, pp. 1191-1210; Cattani, C., The wavelet-based technique in dispersive wave propagation (2003) International Applied Mechanics, 39 (4), pp. 493-501; Cattani, C., Ciancio, A., (2002) Wavelet Analysis of Linear Transverse Acoustic Waves, 80, pp. 1-20. , ISNN; Newland, D.E., (1993) Harmonic Wavelet Analysis. A, 443, pp. 203-225; Mercorelli, P., Rode, M., Terwiesch, P., (2001), System and methodology for dominant frequency detection by using a set of trigonometric wavelet functions. Patent N 7759 in Patentamt ABB Corporate Research Mannheim. Code in the German Patent Office 10 25 89 21. 6Mercorelli, P., Terwiesch, P., A black box identification in harmonic domain (2003) VDE European Transactions on Electrical Power, 13 (1), pp. 29-40; Springer, T.E., Zawoddzinski, T.A., Gottesfeld, S., Polymer electrolyte fuel cell model (1991) Journal of Electrochimical Society, 138 (8), pp. 2334-2342; Muniandy, S.V., Moroz, I.M., Galerkin modelling of the burgers equation using harmonic wavelets (1997) Phys. Lett, A, 235, pp. 352-356 Sponsors: Institute of Electrical Engineering, IEE, UK; University of Perugia, Italy; University of Calgary, Canada; University of Minnesota, MN, ISA; Queens' University of Belfast, UK; International Conference on Computational Science and Its Applications - ICCSA 2006, ICCSA ; Conference date: 08-05-2006 Through 11-05-2006",
year = "2006",
month = jan,
day = "1",
doi = "10.1007/11751540_92",
language = "English",
isbn = "3-540-34070-X",
volume = "1",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "847--856",
editor = "Marina Gavrilova and Osvaldo Gervasi and Vipin Kumar and Tan, {C.J. Kenneth} and David Taniar and Antonio Lagan{\`a} and Youngsong Mun and Hyunseung Choo",
booktitle = "Computational Science and Its Applications – ICCSA 2006",
address = "Germany",

}

RIS

TY - CHAP

T1 - Noise level estimation using haar wavelet packet trees for sensor robust outlier detection

AU - Mercorelli, Paolo

AU - Frick, Alexander

N1 - Conference code: 6

PY - 2006/1/1

Y1 - 2006/1/1

N2 - The paper is related to the on-line noise variance estimation. In practical use, it is important to estimate the noise level from the data rather than to assume that the noise level is known. The paper presented a free thresholding method related to the on-line peak noise variance estimation even for signal with small S/N ratio. The basic idea is to characterize the noise like an incoherent part of the measured signal. This is performed through the wavelet tree by choosing the subspaces where the median value of the wavelet components has minimum. The paper provides to show nice general properties of the wavelet packets on which the proposed procedure is based. The developed algorithm is totally general even though is applied by using Haar wavelet packets and it is present in some industrial software platforms to detect sensor outliers. More, it is currently integrated in the inferential modeling platform of the Advanced Control and Simulation Solution Responsible Unit within ABB’s industry division.

AB - The paper is related to the on-line noise variance estimation. In practical use, it is important to estimate the noise level from the data rather than to assume that the noise level is known. The paper presented a free thresholding method related to the on-line peak noise variance estimation even for signal with small S/N ratio. The basic idea is to characterize the noise like an incoherent part of the measured signal. This is performed through the wavelet tree by choosing the subspaces where the median value of the wavelet components has minimum. The paper provides to show nice general properties of the wavelet packets on which the proposed procedure is based. The developed algorithm is totally general even though is applied by using Haar wavelet packets and it is present in some industrial software platforms to detect sensor outliers. More, it is currently integrated in the inferential modeling platform of the Advanced Control and Simulation Solution Responsible Unit within ABB’s industry division.

KW - Engineering

KW - Noise Variance

KW - Wavelet Packet

KW - Minimum Description Length

KW - Thresholding Method

KW - Wavelet Shrinkage

UR - http://www.scopus.com/inward/record.url?scp=33745951086&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/b1d00728-717d-328c-aacf-48cecd84b6e7/

U2 - 10.1007/11751540_92

DO - 10.1007/11751540_92

M3 - Article in conference proceedings

SN - 3-540-34070-X

SN - 978-3-540-34070-6

VL - 1

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 847

EP - 856

BT - Computational Science and Its Applications – ICCSA 2006

A2 - Gavrilova, Marina

A2 - Gervasi, Osvaldo

A2 - Kumar, Vipin

A2 - Tan, C.J. Kenneth

A2 - Taniar, David

A2 - Laganà, Antonio

A2 - Mun, Youngsong

A2 - Choo, Hyunseung

PB - Springer

CY - Berlin

T2 - International Conference on Computational Science and Its Applications - ICCSA 2006

Y2 - 8 May 2006 through 11 May 2006

ER -

DOI

Zuletzt angesehen

Publikationen

  1. Stepwise-based optimizing approaches for arrangements of loudspeaker in multi-zone sound field reproduction
  2. A geometric approach for controlling an electromagnetic actuator with the help of a linear Model Predictive Control
  3. A localized boundary element method for the floating body problem
  4. Mapping interest rate projections using neural networks under cointegration
  5. The Influence of Note-taking on Mathematical Solution Processes while Working on Reality-Based Tasks
  6. Robust Flatness Based Control of an Electromagnetic Linear Actuator Using Adaptive PID Controller
  7. Gaussian processes for dispatching rule selection in production scheduling
  8. Performance analysis for loss systems with many subscribers and concurrent services
  9. Comments on "Tracking Control of Robotic Manipulators With Uncertain Kinematics and Dynamics"
  10. A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints
  11. An analytical approach to evaluating bivariate functions of fuzzy numbers with one local extremum
  12. On the Nonlinearity Compensation in Permanent Magnet Machine Using a Controller Based on a Controlled Invariant Subspace
  13. An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy
  14. Stability analysis of a linear model predictive control and its application in a water recovery process
  15. Robust Control of Mobile Transportation Object with 3D Technical Vision System
  16. Data-Driven flood detection using neural networks
  17. Passive Peak Voltage Sensor for Multiple Sending Coils Inductive Power Transmission System
  18. A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot
  19. A two-stage Kalman estimator for motion control using model predictive strategy
  20. Continuous 3D scanning mode using servomotors instead of stepping motors in dynamic laser triangulation
  21. A general structural property in wavelet packets for detecting oscillation and noise components in signal analysis
  22. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations
  23. Perfect anti-windup in output tracking scheme with preaction
  24. Simulation based comparison of safety-stock calculation methods
  25. Primary Side Circuit Design of a Multi-coil Inductive System for Powering Wireless Sensors
  26. Continuous and Discrete Concepts for Detecting Transport Barriers in the Planar Circular Restricted Three Body Problem
  27. Convolutional Neural Networks
  28. A New Framework for Production Planning and Control to Support the Positioning in Fields of Tension Created by Opposing Logistic Objectives
  29. Cognitive load and instructionally supported learning with provided and learner-generated visualizations
  30. Using cross-recurrence quantification analysis to compute similarity measures for time series of unequal length with applications to sleep stage analysis
  31. PI and Fuzzy Controllers for Non-Linear Systems
  32. Long-term memory predictors of adult language learning at the interface between syntactic form and meaning
  33. Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning
  34. Modeling and numerical simulation of multiscale behavior in polycrystals via extended crystal plasticity
  35. Transductive support vector machines for structured variables
  36. Switching Dispatching Rules with Gaussian Processes
  37. Introducing parametric uncertainty into a nonlinear friction model
  38. A computational study of a model of single-crystal strain-gradient viscoplasticity with an interactive hardening relation
  39. Multi-view discriminative sequential learning
  40. Combining multiple investigative approaches to unravel functional responses to global change in the understorey of temperate forests
  41. Web-scale extension of RDF knowledge bases from templated websites
  42. Improving short-term academic performance in the flipped classroom using dynamic geometry software
  43. Positioning Improvement for a Laser Scanning System using cSORPD control
  44. An analytical approach to evaluating nonmonotonic functions of fuzzy numbers