DocumentCode
3180373
Title
Application of a novel neural network for identification of nonlinear carbon/carbon gaseous-state deposit process
Author
Yong, Qlang ; JingShe, Li ; Licheng, Jiao
Author_Institution
Key Lab for Radar Signal Process., Xidian Univ., Xi´´an, China
Volume
2
fYear
2002
fDate
26-30 Aug. 2002
Firstpage
1163
Abstract
A novel neural network model and algorithm for highly nonlinear C/C gaseous-state deposit process is presented. The network model consists of fuzzy classifier and some wavelet sub-networks called a hybrid neural network. The input samples are trained by a homologous wavelet network after classifying. The results of the identification of the C/C gaseous-state deposit process are desirable.
Keywords
carbon fibres; chemical engineering computing; learning (artificial intelligence); neural nets; wavelet transforms; carbon/carbon gaseous-state deposit process; fuzzy classifier; homologous wavelet network; hybrid neural network; identification; input sample training; neural network model; nonlinear C/C gaseous-state deposit process; wavelet sub-networks; Building materials; Differential equations; Fuzzy neural networks; Gas industry; Neural networks; Nonlinear systems; Robustness; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2002 6th International Conference on
Print_ISBN
0-7803-7488-6
Type
conf
DOI
10.1109/ICOSP.2002.1179996
Filename
1179996
Link To Document