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Dynamic Structure of Volterra-Wiener Filter for Reference Signal Cancellation in Passive Radar

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Knowledge Engineering, Machine Learning and Lattice Computing with Applications (KES 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7828))

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Abstract

In the article a possibility of using the Volterra-Wiener filter for reference signal elimination in passive radar was considered. The recursive nonlinear orthogonal filter algorithms (with low-complexity and dynamic structures) were developed and implemented within Matlab environment. The results of testing with real-life data are comparable with the effects of the NLMS filter algorithm employment.

Work sponsored by NC3 NATO Agency.

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References

  1. Biernacki, P., Zarzycki, J.: Multidimensional Nonlinear Noise-Cancelling Filters of the Volterra-Wiener Class. In: Proc. 2-Nd Int. Workshop on Multidimensional (nD) Systems (NDS 2000), pp. 255–261. Inst. of Control and Comp. Eng. TU of Zielona Gora Press, Czocha Castle (2000)

    Google Scholar 

  2. Biernacki, P.: Strategies for adaptive nonlinear noise reduction Volterra-Wiener filter structure selection. In: Proc. ICECS 2006, Nice, France, December 10-13 (2006), cd-rom

    Google Scholar 

  3. Haykin, S.: Adaptive filter theory. Prentice Hall, Upper Saddle River (1996)

    Google Scholar 

  4. Lee, D.T.L., Morf, M., Friedlander, B.: Recursive Least-Squares Ladder Estimation Algorithms. IEEE Trans. on CAS 28, 467–481 (1981)

    Article  MathSciNet  Google Scholar 

  5. Zarzycki, J.: Multidimensional Nonlinear Schur Parametrization of NonGaussian Stochastic Signals - Part One: Statement of the Problem. Multidimensional Systems and Signal Processing (MDSSP) Journ. 15(3), 217–241 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  6. Biernacki, P.: A new strategy of adaptive nonlinear echo cancelling Volterra-Wiener filter structure selection. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds.) KES 2010, Part I. LNCS, vol. 6276, pp. 350–359. Springer, Heidelberg (2010)

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Author information

Authors and Affiliations

  1. Telecom, Acoustic and Computer Science Institute, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-350, Wroclaw, Poland

    Pawel Biernacki

Authors
  1. Pawel Biernacki
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Editor information

Editors and Affiliations

  1. Department of Computational Science and Artificial Intelligence, University of the Basque Country, Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  2. Vicomtech-IK4, Paseo Mijeletegui, 20009, San Sebastian, Spain

    Carlos Toro

  3. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  4. School of Engineering, University of Canberra, Mawson Lakes Campus, ACT 2601, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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Biernacki, P. (2013). Dynamic Structure of Volterra-Wiener Filter for Reference Signal Cancellation in Passive Radar. In: Graña, M., Toro, C., Howlett, R.J., Jain, L.C. (eds) Knowledge Engineering, Machine Learning and Lattice Computing with Applications. KES 2012. Lecture Notes in Computer Science(), vol 7828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37343-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-37343-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37342-8

  • Online ISBN: 978-3-642-37343-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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