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https://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 |
DOI: | 10.1023/A:1023538920581 |
Published version: | http://www.springerlink.com/content/v503638530267333/ |
Appears in Collections: | Applied Mathematics publications Aurora harvest 5 |
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