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 :
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