Blind System Identification
In this chapter a comparison of blind system identification methods for linear time-invariant (LTI) systems using HOS is presented . These methods  use only the system output data to identify the system model under the assumption that the system is driven by an independent and identically distributed (i.i.d.) non-Gaussian sequence that is unobservable.
KeywordsMove Average Filter Coefficient Input Distribution ARMA Process Order Cumulants
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- K. S. Lii. Non-gaussian ARMA model identification and estimation. Proc Bus and Econ Statistics (ASA), pages 135–141, 1982.Google Scholar
- K. S. Lii and M. Rosenblatt. Non-gaussian linear processes, phase and deconvolution. Statistical Signal Processing, pages 51–58, 1984.Google Scholar
- K. S. Lii and M. Rosenblatt. A fourth-order deconvolution technique for non-gaussian linear processes. In P. R. Krishnaiah, editor, Multivariate Analysis VI. Elsevier, Amsterdam, The Netherlands, 1985.Google Scholar
- S. L. J. Marple. Digital Spectral Analysis with Applications. Prentice Hall, Englewood Cliffs, New Jersey, 1987.Google Scholar
- A. K. Nandi. On the robust estimation of third-order cumulants in applications of higher-order statistics. Proceedings of IEE, Part F, 140:380–389, 1993.Google Scholar
- A. K. Nandi and J. A. Chambers. New lattice realisation of the predictive least-squares order selection criterion. IEE Proceedings F, 138:545–550, 1991.Google Scholar
- C. L. Nikias. Higher-order spectral analysis. In S. S. Haykin, editor, Advances in Spectrum Analysis and Array Processing, volume I, chapter 7. Prentice Hall, Englewood Cliffs, New Jersey, 1991.Google Scholar
- C. L. Nikias and J. M. Mendel. Signal procesing with higher-order spectra. IEEE Signal Processing Magazine, pages 10 – 37, 1993.Google Scholar
- J. K. Richardson. Parametric modelling for linear system identification and chaotic system noise reduction. PhD thesis, University of Strathclyde, Glasgow, UK, 1996.Google Scholar
- I. The MathWorks. HOSA toolbox for use with MATLAB.Google Scholar