The Implementation of FEM and RBF Neural Network in EIT

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. Mathem...

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Bibliographic Details
Published in2009 Second International Conference on Intelligent Networks and Intelligent Systems pp. 66 - 69
Main Authors Peng Wang, Hong-li Li, Li-li Xie, Yi-cai Sun
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Conductivity measurement
Electrical impedance tomography
Equations
Finite element method
Finite element methods
Image reconstruction
Impedance
Intelligent networks
Inverse problems
Neural networks
RBF neural network
semiconductor section resistivity
Tomography
Voltage
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Summary: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.
ISBN:142445557X
9781424455577
DOI:10.1109/ICINIS.2009.26