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PubMed · 2223893

Structural classification of multi-input nonlinear systems.

H W Chen·L D Jacobson·J P Gaska
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Abstract

We present new structural classification and parameter estimation results that are applicable to multi-input nonlinear systems. The mathematical relationships between the self- and cross-(Volterra and Wiener) kernels are derived for a basic two-input nonlinear structure. These results are then used to develop classification methods for more complicated two-input structures. Algorithms for estimating the parameters (linear and nonlinear subsystems) of these structures are also presented.

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CyberneticsLinear ModelsJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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H W Chen, L D Jacobson, J P Gaska. 1990. Structural classification of multi-input nonlinear systems.. https://doi.org/10.1007/bf00202751

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