Title :
Approximation capabilities of hierarchical hybrid systems
Author :
Zeng, Xiao-Jun ; Keane, John A.
Author_Institution :
Sch. of Informatics, Univ. of Manchester
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;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/TSMCA.2006.878972