DocumentCode :
2855579
Title :
The Implementation of FEM and RBF Neural Network in EIT
Author :
Wang, Peng ; Li, Hong-li ; Li-li Xie ; Sun, Yi-cai
Author_Institution :
Sch. of Comput. Sci. & Eng., Hebei Univ. of Technol., Tianjin, China
fYear :
2009
fDate :
1-3 Nov. 2009
Firstpage :
66
Lastpage :
69
Abstract :
With the rapid development of electronic technology, semiconductor section resistivity measurement is receiving increasing attention. This paper applies electrical impedance tomography (EIT) technology to semiconductor resistivity measurements. FEM is applied to solve the EIT forward problem. Mathematical description of partial differential equation, equivalent variation differential problem, element characteristic matrix and the assembly rule of general matrix are given for calculation. To solve the EIT inverse problem, a new method of image reconstruction algorithm based on RBF neural network is proposed. This method can well adapt to non-linear and ill-posed characteristics of EIT. The simulation experiment results indicate that the RBF algorithm can improve the reconstruction image´s quality and the accuracy obviously.
Keywords :
electric impedance imaging; electronic engineering computing; finite element analysis; image reconstruction; partial differential equations; radial basis function networks; RBF neural network; electrical impedance tomography technology; electronic technology; element characteristic matrix; equivalent variation differential problem; finite element method; image quality reconstruction; partial differential equation; semiconductor section resistivity measurement; Conductivity measurement; Equations; Finite element methods; Image reconstruction; Impedance; Intelligent networks; Inverse problems; Neural networks; Tomography; Voltage; Electrical impedance tomography; Finite element method; RBF neural network; semiconductor section resistivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
Type :
conf
DOI :
10.1109/ICINIS.2009.26
Filename :
5365675
Link To Document :
بازگشت