DocumentCode
1161611
Title
Approximation capabilities of hierarchical hybrid systems
Author
Zeng, Xiao-Jun ; Keane, John A.
Author_Institution
Sch. of Informatics, Univ. of Manchester
Volume
36
Issue
5
fYear
2006
Firstpage
1029
Lastpage
1039
Abstract
This paper investigates the approximation capabilities of hierarchical hybrid systems, which are motivated by research in hierarchical fuzzy systems, hybrid intelligent systems, and modeling of model partly known systems. For a function (system) with known hierarchical structure (i.e., one that can be represented as a composition of some simpler and lower dimensional subsystems), it is shown that hierarchical hybrid systems have the structure approximation capability in the sense that such a hybrid approximation scheme can approximate both the overall system and all the subsystems to any desired degree of accuracy. For a function (system) with unknown hierarchical structure, Kolmogorov´s theorem is used to construct the hierarchical structure of the given function (system). It is then shown that hierarchical hybrid systems are universal approximators
Keywords
function approximation; fuzzy systems; hierarchical systems; neural nets; approximation capabilities; function system; hierarchical fuzzy systems; hierarchical hybrid system; hybrid intelligent systems; Approximation methods; Fuzzy systems; Hierarchical systems; Hybrid intelligent systems; Intelligent networks; Mathematical model; Neural networks; Pattern recognition; Power system modeling; Predictive models; Fuzzy systems; hierarchical systems; hybrid intelligent systems; neural networks; universal approximation;
fLanguage
English
Journal_Title
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher
ieee
ISSN
1083-4427
Type
jour
DOI
10.1109/TSMCA.2006.878972
Filename
1678030
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