Application of PSO Algorithm and RBF Neural Network in Electrical Impedance Tomography

摘要：

To measure the resistivity distribution of semiconductor wafers,this article applies electrical impedance tomography (EIT) technology to semiconductor resistivity measurements. A new method of Image reconstruction algorithm based on RBF neural network for EIT is proposed. The particle swarm optimization algorithm (PSO) is designed to optimize the RBF networks connection weights. The simulation experiment results for 32 electrodes EIT data collecting system indicate that the PSO-RBF algorithm can improve the reconstruction image quality and the accuracy obviously,and that it is feasible of using RBF mural network to measure the resistivity distribution of semiconductor wafers.

关键词： electrical impedance tomography RBF neural network particle swarm optimization connection weights adjustment reconstruction image

作者: Peng Wang Lili Xie Yicai Sun

作者单位: School of Information Engineering,Hebei University of Technology,Tianjin 300401,China Electronic and Information Engineering,Tianjin Vocational Institute,Tianjin 300410,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 1594-1598

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）