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Blind System Identification

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Blind Estimation Using Higher-Order Statistics

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Abstract

In this chapter a comparison of blind system identification methods for linear time-invariant (LTI) systems using HOS is presented [37]. These methods [35] 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.

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Authors
  1. J. K. Richardson
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  2. A. K. Nandi
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Electronics, University of Liverpool, UK

    Asoke Kumar Nandi (David Jardine Chair of Electrical Engineering) (David Jardine Chair of Electrical Engineering)

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© 1999 Springer Science+Business Media Dordrecht

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Richardson, J.K., Nandi, A.K. (1999). Blind System Identification. In: Nandi, A.K. (eds) Blind Estimation Using Higher-Order Statistics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2985-6_3

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  • DOI: https://doi.org/10.1007/978-1-4757-2985-6_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5078-9

  • Online ISBN: 978-1-4757-2985-6

  • eBook Packages: Springer Book Archive

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