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Adaptive blind system identification using weighted cumulant slices
Author(s) -
Vidal Josep,
Fonollosa José A. R.
Publication year - 1996
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199603)10:2/3<213::aid-acs348>3.0.co;2-z
Subject(s) - autoregressive–moving average model , impulse response , blind deconvolution , algorithm , system identification , mathematics , finite impulse response , moving average , adaptive filter , computer science , recursion (computer science) , lemma (botany) , deconvolution , control theory (sociology) , autoregressive model , artificial intelligence , statistics , mathematical analysis , data mining , ecology , poaceae , control (management) , biology , measure (data warehouse)
Many linear methods have been proposed in the literature to blindly estimate the ARMA parameters of a time series using HOS. Nevertheless, they are mainly off‐line and not much has been done in the adaptive case. The method proposed in this contribution is the adaptive version of the w‐slice method. The recursion is based on the inversion lemma when attempting the solution of an underdetermined matrix equation. The system impulse response can be recovered regardless of the ARMA or MA character of the system. The number of operations depends on the square of the system order and is considerably reduced with respect to previous approaches. Application to channel deconvolution is shown.