Title :
Nonlinear systems using two-layer DBF neural networks and application for model identification structure
Author :
Wen-Ming, Cao ; Lu Fei ; Hao, Feng ; Shuojue, Wang
Author_Institution :
Inst. of Intell. Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
fDate :
Aug. 31 2004-Sept. 4 2004
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 that persistency of excitation condition is fulfilled. The multiple model identification structure is analyzed.
Keywords :
feedforward neural nets; neural nets; nonlinear systems; state estimation; direction basis function neural network; model identification structure; nonlinear system; state estimation error; two-layer DBF neural network; Convergence; Educational institutions; Electrostatic precipitators; Estimation error; Filtering; Hardware; Multi-layer neural network; Neural networks; Neurons; Nonlinear systems;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1452729
