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《Pattern Recognition and Artificial Intelligence》 2004-01
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NEURAL NETWORK MODELS FOR ELECTRICAL IMPEDANCE TOMOGRAPHY

Nan Guofang ( Institute of Systems Engineering , Tianjin University, Tianjin 300072)  
Duo to slow imaging speed and images got being unable to represent real impedance distribution of sensitive field in some case by traditional electrical impedance tomography algorithms, two models base on different neural networks (BP neural network and RBF neural network) and their image reconstruction algorithms for electrical impedance tomography are presented in this paper. Result illustrate that image reconstruction algorithms based on neural network model are superior in speed and quality to traditional algorithms.
【CateGory Index】: TP183
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【Citations】
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