Analysis of stochastic gradient tracking of time-varying polynomial Wiener systems

This paper presents analytical and Monte Carlo results for a stochastic gradient adaptive scheme that tracks a time-varying polynomial Wiener (1958) system [i.e., a linear time-invariant (LTI) filter with memory followed by a time-varying memoryless polynomial nonlinearity]. The adaptive scheme cons...

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Veröffentlicht in:	IEEE transactions on signal processing 2000-06, Vol.48 (6), p.1676-1686
Hauptverfasser:	Bershad, N.J., Celka, P., Vesin, J.-M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive filters Algorithms Computer simulation Economic models Least squares approximation Monte Carlo methods Nonlinear filters Nonlinearity Optimization Phase estimation Polynomials Recursion Stochastic processes Stochastic systems Stochasticity Studies Time varying systems Tracking Wiener filter
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