CFP last date
20 May 2024
Reseach Article

Modeling, simulation and signal processing for Control room EMI problem using frequency domain Approach and Bayesian estimation

by Vidya R. Keshwani, Naveeta Kant, Kallol Roy
journal cover thumbnail
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 15
Year of Publication: 2010
Authors: Vidya R. Keshwani, Naveeta Kant, Kallol Roy
10.5120/312-479

Vidya R. Keshwani, Naveeta Kant, Kallol Roy . Modeling, simulation and signal processing for Control room EMI problem using frequency domain Approach and Bayesian estimation. International Journal of Computer Applications. 1, 15 ( February 2010), 112-119. DOI=10.5120/312-479

@article{ 10.5120/312-479,
author = { Vidya R. Keshwani, Naveeta Kant, Kallol Roy },
title = { Modeling, simulation and signal processing for Control room EMI problem using frequency domain Approach and Bayesian estimation },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 15 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 112-119 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number15/312-479/ },
doi = { 10.5120/312-479 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:43:28.105100+05:30
%A Vidya R. Keshwani
%A Naveeta Kant
%A Kallol Roy
%T Modeling, simulation and signal processing for Control room EMI problem using frequency domain Approach and Bayesian estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 15
%P 112-119
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The problem of separation of mixed signal spectrum is encountered in many engineering systems. One such problem is a problem of electromagnetic topology wherein mixed signals at spatial points are encountered and one would like to separate them out using digital signal processing tools. This paper discusses techniques such as fast Fourier transform, short term Fourier transform, wavelet transform and Hilbert Huang transform in light of this application. Advantages and limitations of each technique are bought out for above said problem.

References
  1. Brown, R. G.,P. Y. C. Hwang., Introduction to Random Signals and Applied Kalman Filtering, John Wiley and Sons, Inc, 1992.
  2. I. Daubechies, "Orthonormal Bases of Compactly Supported Wavelets", Comm. Pure Appl. Math, Vol. 41, 1988.
  3. Daniel Fleisch, A Student's Guide to Maxwell's Equations, Cambridge University Press , 2008
  4. Bernard Friedland, "Treatment of Bias in Recursive Filtering", IEEE Transactions on Automatic control, AC-14 no. 4, August 1969, pp. 359-367.
  5. Gelb, A., Applied Optimal Estimation, MIT Press, Cambridge, MA, 1974.
  6. John E. Gray, Ronald E. Helmick, "A state space approach to determining solution to Maxwell's for a one-dimensional dispersive medium", IEEE proc. Elec. Comp, 1991.
  7. Peter S. Maybeck, Stochastic models, estimation and control", Academic Press, New York, 1979.
  8. Norden E. Huang, Zheng Shen, Steven R. Long, Manli C. Wu, Hsing H. Liu Shih, Quanan Zheng, Nai-Chyuan Yen, Chi Chao Tung8 and Henry H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis", Proc. of IR. Soc. Lond. A, October 1998 454, pp. 903-955.
  9. Olivier Rioul and Martin Vetterlli, "Wavelets and signal processing", IEEE transactions on signal processing, October 1991, pp. 5-6.
  10. Dragan Poljak, Advanced modeling in computational electromagnetic compatibility, Wiley Interscience A John Wiley Sons, Inc., Publication.
  11. George M. Siouris, An engineering approach to optimal control and estimation theory, A Wiley Interscience publication John Wiley and Sons Inc New York.
  12. William H. Hayt, John A. Buck, Engineering electromagnetics, 4th edition.
Index Terms

Computer Science
Information Sciences

Keywords

Signal wavelets Kalman filter