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https://hdl.handle.net/2440/590
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dc.contributor.author | Torokhti, A. | - |
dc.contributor.author | Howlett, P. | - |
dc.contributor.author | Pearce, C. | - |
dc.date.issued | 2003 | - |
dc.identifier.citation | Multidimensional Systems and Signal Processing, 2003; 14(4):397-410 | - |
dc.identifier.issn | 0923-6082 | - |
dc.identifier.uri | http://hdl.handle.net/2440/590 | - |
dc.description | The original publication is available at www.springerlink.com | - |
dc.description.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. | - |
dc.description.statementofresponsibility | Anatoli Torokhti, Phil Howlett and Charles Pearce | - |
dc.language.iso | en | - |
dc.publisher | Kluwer Academic Publ | - |
dc.source.uri | http://www.springerlink.com/content/v503638530267333/ | - |
dc.subject | pseudo-inverse matrix - stochastic signals - covariance matrix - matrix computation - functional minimization | - |
dc.title | Method of hybrid approximations for modelling of multidimensional nonlinear systems | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1023/A:1023538920581 | - |
pubs.publication-status | Published | - |
Appears in Collections: | Applied Mathematics publications Aurora harvest 5 |
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