Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/590
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Type: Journal article
Title: Method of hybrid approximations for modelling of multidimensional nonlinear systems
Author: Torokhti, A.
Howlett, P.
Pearce, C.
Citation: Multidimensional Systems and Signal Processing, 2003; 14(4):397-410
Publisher: Kluwer Academic Publ
Issue Date: 2003
ISSN: 0923-6082
Statement of
Responsibility: 
Anatoli Torokhti, Phil Howlett and Charles Pearce
Abstract: In this paper we propose a new approach to the constructive mathematical representation of nonlinear systems transforming stochastic signals. The approach is based on a combination of a new best approximation technique and a new iterative procedure. For each iteration, the approximation is constructed as a polynomial operator of degree r which minimizes the mean–squared error between a desired output signal and the output signal of the approximating system. We show that this hybrid technique produces a computationally efficient and flexible method for modelling of nonlinear systems. The method has two degrees of freedom, the degree r of the approximating operator and the number of iterations, to decrease the associated error.
Keywords: pseudo-inverse matrix - stochastic signals - covariance matrix - matrix computation - functional minimization
Description: The original publication is available at www.springerlink.com
RMID: 0020030662
DOI: 10.1023/A:1023538920581
Published version: http://www.springerlink.com/content/v503638530267333/
Appears in Collections:Applied Mathematics publications

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