Grimble, M.J. and Ali Naz, S. (2010) Optimal minimum variance estimation for nonlinear discrete-time multichannel systems. IET Signal Processing, 4 (6). pp. 618-629.Full text not available in this repository. (Request a copy from the Strathclyde author)
A non-linear operator approach to estimation in discrete-time multivariable systems is described. It involves inferential estimation of a signal which enters a communication channel that contains non-linearities 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 non-linear estimation problem is obtained using nonlinear operators. The signal and noise channels may be grossly non-linear and are represented in a very general non-linear operator form. The resulting so-called Wiener non-linear minimum variance estimation algorithm is relatively simple to implement. The optimal non-linear estimator is derived in terms of the nonlinear operators and can be implemented as a recursive algorithm using a discrete-time non-linear difference equation. In the limiting case of a linear system, the estimator has the form of a Wiener filter in discrete-time polynomial matrix system form. A non-linear channel equalisation problem is considered for the design example.
|Keywords:||channel estimation, equalisers, polynomial matrices, stochastic processes, Electrical engineering. Electronics Nuclear engineering, Signal Processing, Electrical and Electronic Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering|
|Depositing user:||Pure Administrator|
|Date Deposited:||15 Sep 2011 14:21|
|Last modified:||06 Jan 2017 09:57|