DocumentCode
2538760
Title
System Identification of TP Film Evaporation by Using Nearly Equivalent NN Model
Author
Huang, Du-Jou ; Huang, Chih-Chien ; Chen, Yu-Ju ; Huang, Huang-Chu ; Chen, Shen-Whan ; Hwang, Rey-Chue
Author_Institution
Electr. Eng. Dept., I-Shou Univ., Kaohsiung, Taiwan
fYear
2010
fDate
13-15 Dec. 2010
Firstpage
118
Lastpage
121
Abstract
This paper presents a technique, called “nearly equivalent neural network (NN) model” in the application of nonlinear system identification. This technique is expected to adequately to catch the behavior of the nonlinear system. To demonstrate the new technique proposed, the evaporation system of TP decoration film was analyzed. The complex relationship between the film´s transmittance and its possible influencing factors was identified. For the comparison, the same simulations were also performed by using the conventional neural network with the standard steepest descent error back-propagation (BP) learning algorithm.
Keywords
identification; neural nets; nonlinear systems; thin films; touch sensitive screens; vacuum deposition; TP decoration film; error backpropagation learning algorithm; evaporation system; film transmittance; nearly equivalent neural network model; nonlinear system identification; Artificial neural networks; Mathematical model; Neurons; Optimization; Polynomials; System identification; Training; nearly equivalent neural network; system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4244-8891-9
Electronic_ISBN
978-0-7695-4281-2
Type
conf
DOI
10.1109/ICGEC.2010.37
Filename
5715385
Link To Document