DocumentCode
423912
Title
Identification of nonlinear systems using two-layer DBF neural networks
Author
Feng, Hao ; Cao, Wen-Ming ; Wang, Shuo-Jue
Author_Institution
Jiaxing Coll., Zhejiang, China
Volume
1
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
488
Abstract
Nonlinear system identification using direction basis function neural networks is presented. The state estimation error is proven to converge to zero asymptotically. Parameters of the identifier converge to the ideal parameters provided by that persistency of excitation condition is fulfilled. Its identification structure is analyzed.
Keywords
convergence; neural nets; neurocontrollers; nonlinear control systems; state estimation; direction basis function; nonlinear system identification; state estimation error; two-layer DBF neural network; Computer errors; Differential equations; Educational institutions; Intelligent networks; Neural networks; Neurons; Nonlinear equations; Nonlinear systems; Pattern recognition; State estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380739
Filename
1380739
Link To Document