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Tytuł artykułu

Statistical view on phase and magnitude information in signal processing

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this work the problem of reconstruction of an original complex-valued signal ot, t = 0, 1,...,n - 1, from its Discrete Fourier Transform (DFT) spectrum corrupted by random fluctuations of magnitude and/or phase is investigated. It is assumed that the magnitude and/or phase of discrete spectrum values are distorted by realizations of uncorrelated random variables. The obtained results of analysis of signal reconstruction from such distorted DFT spectra concern derivation of the expected values and bounds on variances of the reconstructed signal at the observation moments. It is shown that the considered random distortions in general entail change in magnitude and/or phase of the reconstructed signal expected values, which together with imposed random deviations with finite variances can blur the similarity to the original signal. The effect of analogous random amplitude and/or phase distortions of a complex valued time domain signal on band pass filtration of distorted signal is also investigated.
Rocznik
Strony
127--136
Opis fizyczny
Bibliogr. 21 poz.
Twórcy
autor
  • Space Research Centre, PAS
Bibliografia
  • Blackledge J. M. (2003). Digital Signal Processing, Horwood Publishing, Chichester, West Sussex, England.
  • Bloomfield P. (2000). Fourier Analysis of Time Series: An Introduction, Wiley, New York.
  • Braun W. J., Kulperger R. J. (1997). Properties of a Fourier Bootstrap Method for Time Series, Communications in Statistics - Theory and Methods, 26(6), 1329-1335.
  • Bremaud P. (2002). Mathematical Principles of Signal Processing: Fourier and Wavelet Analysis, Springer Verlag Inc., New York.
  • Brillinger D. R. (1975). Time Series - Data Analysis and Theory, Holt, Rinehart and Winston Inc., New York.
  • Cooley J. W. and Tukey J. W. (1965). An Algorithm for the Machine Calculation of Complex Fourier Series, Mathematics of Computation, 19, 297-301.
  • Gasquet C., Witomski P. (1999). Fourier Analysis and Applications - Filtering, Numerical Computation, Wavelets, Springer Verlag Inc., New York.
  • Hansen P. Ch., Nagy J. G., O’Leary D. P. (2006). Deblurring Images, Matrices, Spectra and Filtering, SIAM, Philadelphia.
  • Hayes M., Lim J., Oppenheim A. (1980). Signal Reconstruction from Phase or Magnitude, IEEE Transactions on Acoustics Speech and Signal Processing, ASSP-28(6), pp. 672-680.
  • Hoggar S. D. (2006). Mathematics of Digital Images - Creation, Compression, Restoration, Recognition, Cambridge University Press, Cambridge.
  • Johnson N.L., Kotz S., Balakrishnan N. (1994). Continuous Univariate Distributions, Vol. 1-2, John Wiley & Sons, New York.
  • Koopmans L. H. (1974). The Spectral Analysis of Time Series, Academic Press, New York.
  • Mammen E. and Nandi S. (2008). Some Theoretical Properties of Phase-Randomized Multivariate Surrogates, Statistics, 42(3), 195-205.
  • Ni X. and Huo X. (2007). Statistical Interpretation of the Importance of Phase Information in Signal and Image Reconstruction, Statistics and Probability Letters, 77(4), 447-454.
  • Oppenheim A. V., Lim J. S. (1981). The Importance of Phase in Signals, Proceedings of the IEEE, 69(5), 529-541.
  • Popiński W. (1997). On Consistency of Discrete Fourier Analysis of Noisy Time Series, Artificial Satellites - Journal of Planetary Geodesy, 32(3), 131-142.
  • Popiński W. (2008). Insight into the Fourier Transform Band Pass Filtering Technique, Artificial Satellites - Journal of Planetary Geodesy, 43(4), 129-141.
  • Popiński W. (2010). On Discrete Fourier Spectrum of Randomly Modulated Signals, Artificial Satellites - Journal of Planetary Geodesy, 45(3), 143-152.
  • Press W. H., Flannery B. P., Teukolsky S. A., and Vetterling W. T. (1992). Numerical Recipes - The Art of Scientific Computing, Cambridge University Press, Cambridge.
  • Schreiber T., Schmitz A. (2000). Surrogate Time Series, Physica D, 142(3-4), 346-382.
  • Singleton R. C. (1969). An Algorithm for Computing the Mixed Radix Fast Fourier Transform, IEEE Transactiions on Audio and Electroacoustics, AU-17(2), 93-103.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-20cf35f8-5b6a-44b6-aec4-c0b56fe83652
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