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
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;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1179996
