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Blind separation of delayed sources based on second-order Taylor approximation

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Warianty tytułu
PL
Ślepa separacja sygnałów bazująca na aproksymacji Taylora drugiego rzędu
Języki publikacji
EN
Abstrakty
EN
Conventional linear instantaneous mixing model becomes unsuitable if propagation time delays are taken into account. A blind separation algorithm based on second-order Taylor approximation for delayed sources (SOTADS) is presented, under the constraint that time delays are small in comparison with the coherence time of each source. Simulation results validate that the proposed algorithm performs superior than related approaches even when the constraint is violated.
PL
Zaprezentowano algorytm ślepej separacji bazujący na aproksymacji Taylora drugiego rzędu dla źródeł z opóźnieniem SOTADS. Założono że czas opóźnienia jest mały w porównaniu z czasem koherencji obu źródeł.
Rocznik
Strony
253--256
Opis fizyczny
Bibliogr. 16 poz., wykr.
Twórcy
autor
  • Institute of Communications Engineering, PLA University of Science and Technology
autor
  • Institute of Communications Engineering, PLA University of Science and Technology
autor
  • Institute of Communications Engineering, PLA University of Science and Technology
Bibliografia
  • [1] A. Hyvarinen, J. Karhunen and E. Oja, Independent component analysis, New York: John Wiley & Sons, 2001.
  • [2] V. Zarzoso and P. Comon, Robust independent component analysis by iterative maximization of the kurtosis contrast with algebraic optimal step size, IEEE Trans. Neural Network, vol.21, no.2, pp.248-261, 2010.
  • [3] F. Nesta, P. Svaizer and M. Omologo, Convolutive BSS of short mixtures by ICA recursively regularized across frequencies, IEEE Trans. Audio, Speech and Lauguage Processing, vol.19, no.3, pp.624-639, 2011.
  • [4] K. Torkkola, Blind separation of delayed and convolved sources, Unsupervised Adaptive Filtering, New York: Wiley, 2000, vol.1, pp.321-375.
  • [5] A. Yeredor, Blind source separation with pure delay mixtures, In International Workshop on independent component analysis and blind source separation Conference, San Diego,CA, 2001.
  • [6] L. Omlor and M. S. Giese, Blind source separation for overdetermined delayed mixtures’, in Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, pp.1049-1056, 2007b.
  • [7] D. Nion, B. Vandewoestyne, S. Vanaverbeke, et.al, A timefrequency technique for blind separation and localization of pure delayed sources, in Proceedings of the 9th international conference on latent variable analysis and signal separation, pp.546-554, 2010.
  • [8] N. Jiang and D. Farina, Covariance and time-scale methods for blind separation of delayed sources, IEEE Trans. On Biomedical Engineering, vol.58, no.3, pp.550-556, 2011.
  • [9] G. Chabriel and J. Barrere, Blind indentification of slightly delayed mixtures’, in Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing, pp. 319–323, 2000.
  • [10] J. Ashtar, et al, A novel approach to blind separation of delayed sources in linear mixture, in 7th Semester Signal Processing, Aalborg, Denmark, pp.1-8, 2004.
  • [11] G. Chabriel and J. Barrere, An instantaneous formulation of mixtures for blind separation of propagating waves, IEEE Trans. Signal Processing, vol.54, no.1, pp.49-58, 2006.
  • [12] J. Barrere and G. Chabriel: ‘A compact sensor array for blind separation of sources’, IEEE Trans. On Circuits and Systems-I: Fundamental Theory and Applications, 2002, vol.49, no.5, pp.565-574.
  • [13] A. Belouchrani, et al, : ‘A blind source separation technique using second-order statistics’, IEEE Trans. Signal Processing, 1997, vol.45, no.2, pp.434-444.
  • [14] G. H. Golub and C. F. V. Loan, Matrix Computations, Baltimore, MD: Johns Hopkins Univ. Press, 1989.
  • [15] A. Papoulis, Probability, Random Variables, and Stochastic Process, 2nd ed, New York: McGraw-Hill, 1984.
  • [16] K. S. Shanmugan and A. M. Breipohl, Random Signals, New York: Wiley, 1988.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5e47ea68-7169-4814-b4d2-ad1b983d7517
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