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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-22c2a376-2d4a-46ff-abbd-ab9567535f39

Czasopismo

Computer Applications in Electrical Engineering

Tytuł artykułu

Estimation of the noise variance in time series using a median filter

Autorzy Pęksiński, J.  Mikołajczak, G. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Information about the level of signal interference, allows you to select the appropriate method pre-processing information. Assuming that the disturbance is a process additive, a normal distribution can do this using the smoothing filters, and in particular the median filter. This paper presents a method of estimating the level of disturbance, based on median filtration and the assumption that the smoothing process applies to noise, exclusively. The knowledge of a noise reduction coefficient enables the determining of an estimated quantity.
Słowa kluczowe
EN noise variation estimation   median filter  
Wydawca Wydawnictwo Politechniki Poznańskiej
Czasopismo Computer Applications in Electrical Engineering
Rocznik 2014
Tom Vol. 12
Strony 316--323
Opis fizyczny Bibliogr. 10 poz., rys., tab.
Twórcy
autor Pęksiński, J.
autor Mikołajczak, G.
  • West Pomeranian University of Technology 71-126 Szczecin, ul. 26 Kwietnia 10
Bibliografia
[1] L. Ljung, System identification theory for User. Prentice-Hall, Englewood CliPs, NJ, 1987.
[2] H. Poor, An Introduction to Signal Detection and Estimation. New York: Springer-Verlag, 1985.
[3] P.G. Ferrario, Local Variance Estimation for Uncensored and Censored Observations, Springer Vieweg, 2013.
[4] S.K. Mitra, J.F.Kaiser, Handbook Digital Signal Processing, John Willey 1993.
[5] A. Jones, "New tools in non-linear modelling and prediction," Computational Management Science, vol. 1, no. 2, pp. 109-149, Jul. 2004.
[6] M. Neumann, "Fully data-driven nonparametric variance estimators" Statistics, vol. 25, pp. 189-212, 1994.
[7] J. Kowalski,J. Peksinski, G. Mikolajczak, "Detection of noise in digital images by using the averaging filter name COV" Intelligent Information and Database Systems 5th Asian Conference, ACIIDS 2013, Proceedings, Pt. 2 eds.: Ali Selamat, Ngoc Thanh Nguyen, Habibollah Haron Berlin [i in.] : Springer, pp. 1-8 2013.
[8] H. Pi and C. Peterson, "Finding the embedding dimension and variable dependencies in time series, Neural Computation, vol. 6, no. 3, pp.509-520, 1994.
[9] E. Eirola, E. Liiti¨ainen, A. Lendasse, F. Corona, and M. Verleysen, "Using the delta test for variable selection," in ESANN 2008, European Symposium on Artificial Neural Networks, Bruges (Belgium), pp. 25-30 2008.
[10] J. Peksinski, M. Stefanowski, G. Mikolajczak, Estimating the level of noise in digital images. Intelligent multimedia technologies for networking applications: techniques and tools ed. Dimitris N. Kanellopoulos Information Science Reference, pp. 409-433, 2013.
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