Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Method of hybrid approximations for modelling of multidimensional nonlinear systems|
|Citation:||Multidimensional Systems and Signal Processing, 2003; 14(4):397-410|
|Publisher:||Kluwer Academic Publ|
|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|
|Appears in Collections:||Applied Mathematics publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.