School of Electronics and Information Engineering, Sichuan University, Chengdu, China

---

Abstract—Effective complex permittivity measurements of materials are important in microwave engineering and microwave chemistry. The BP (Back Propagation) neural network computational module has been applied to microwave technology and becomes a useful tool recently. A neural network can be trained to learn the behavior of an effective complex permittivity of material under microwave irradiation in an experimental system. It can provide a fast and accurate result for the material permittivity. Thus, the on-line measurement has been realized. In this paper, a measurement system has been designed and the S-parameters are obtained by full-wave simulations to reconstruct the material permittivity. Moreover, several organic solvents have been measured. The relative errors of the reconstructed results for several organic solvents are less than 5% compared with reference data. The reconstructed results of the effective permittivities of solvents by means of the BP neural network are obtained quickly and accurately.

Index Terms—BP (Back Propagation); Neural network; Effective permittivity; Measurement

[PDF]

Cite: Qian Chen, Kama Huang, Xiaoqing Yang, Ming Luo, Huacheng Zhu, "A BP Neural Network Realization in the Measurement of Material Permittivity," Journal of Software vol. 6, no. 6, pp. 1089-1095, 2011.