Non-linear minimum variance estimation for discrete-time multi-channel systems

Mike J. Grimble, Shamsher Ali Naz

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A nonlinear operator approach to estimation in discrete-time systems is described. It involves inferential estimation of a signal which enters a communications channel involving both nonlinearities and transport delays. The measurements are assumed to be corrupted by a colored noise signal which is correlated with the signal to be estimated. The system model may also include a communications channel involving either static or dynamic nonlinearities. The signal channel is represented in a very general nonlinear operator form. The algorithm is relatively simple to derive and to implement.
LanguageEnglish
Pages2437-2444
Number of pages7
JournalIEEE Transactions on Signal Processing
Volume57
Issue number7
DOIs
Publication statusPublished - Jul 2009

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Mathematical operators

Keywords

  • estimation
  • filtering
  • minimum-variance
  • nonlinear
  • optimal estimation
  • optimization
  • quadratic cost

Cite this

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abstract = "A nonlinear operator approach to estimation in discrete-time systems is described. It involves inferential estimation of a signal which enters a communications channel involving both nonlinearities and transport delays. The measurements are assumed to be corrupted by a colored noise signal which is correlated with the signal to be estimated. The system model may also include a communications channel involving either static or dynamic nonlinearities. The signal channel is represented in a very general nonlinear operator form. The algorithm is relatively simple to derive and to implement.",
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Non-linear minimum variance estimation for discrete-time multi-channel systems. / Grimble, Mike J.; Naz, Shamsher Ali.

In: IEEE Transactions on Signal Processing, Vol. 57, No. 7, 07.2009, p. 2437-2444.

Research output: Contribution to journalArticle

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AB - A nonlinear operator approach to estimation in discrete-time systems is described. It involves inferential estimation of a signal which enters a communications channel involving both nonlinearities and transport delays. The measurements are assumed to be corrupted by a colored noise signal which is correlated with the signal to be estimated. The system model may also include a communications channel involving either static or dynamic nonlinearities. The signal channel is represented in a very general nonlinear operator form. The algorithm is relatively simple to derive and to implement.

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KW - filtering

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KW - optimal estimation

KW - optimization

KW - quadratic cost

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