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Abstract
A nonlinear operator approach to estimation in discretetime multivariable systems is described. It involves inferential estimation of a signal which enters a communication channel that contains nonlinearities and transport delays. The measurements are assumed to be corrupted by a coloured noise signal correlated with the signal to be estimated. The solution of the nonlinear estimation problem is obtained using nonlinear operators. The signal and noise channels may be grossly nonlinear and are represented in a very general nonlinear operator form. The resulting socalled Wiener nonlinear minimum variance estimation algorithm is relatively simple to implement. The optimal nonlinear estimator is derived in terms of the nonlinear operators and can be implemented as a recursive algorithm using a discretetime nonlinear difference
equation. In the limiting case of a linear system, the estimator has the form of a Wiener filter in discretetime polynomial matrix system form. A nonlinear channel equalisation problem is considered for the design example.
equation. In the limiting case of a linear system, the estimator has the form of a Wiener filter in discretetime polynomial matrix system form. A nonlinear channel equalisation problem is considered for the design example.
Original language  English 

Pages (fromto)  618629 
Number of pages  12 
Journal  IET Signal Processing 
Volume  4 
Issue number  6 
DOIs  
Publication status  Published  Dec 2010 
Keywords
 channel estimation
 equalisers
 polynomial matrices
 stochastic processes
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Dive into the research topics of 'Optimal minimum variance estimation for nonlinear discretetime multichannel systems'. Together they form a unique fingerprint.Projects
 2 Finished

INDUSTRIAL NONLINEAR CONTROL AND REALTIME APPLICATIONS
Grimble, M., Katebi, R. & Ordys, A.
EPSRC (Engineering and Physical Sciences Research Council)
1/05/05 → 30/04/10
Project: Research