Modeling Approach for Distributed RF MEMS Phase Shifter based on IA-BP Neural Network

摘要：

An Efficient modeling technique based on immune algorithm and BP neural network is presented for the design of RF MEMS phase shifter. Three sensitive parameters are selected according to complicated three-dimensional structure design of an RF MEMS phase shifter and used as inputs of neural network. In the model, immune algorithm is first used for global search and then BP algorithm for local search. Experiments show that the proposed approach in this paper is a high efficiency modeling for the RF characteristics analysis for up/down-state of RF MEMS phase shifter. Comparison between improved BP neural network predictions and HFSS simulations show that the root mean square errors, mean absolute errors and maximize absolute errors are less than 1.77dB(534o), 2.24dB(5.93o) and 2.60dB(6.19o) respectively. Also, improved BP neural network reduces the training time at least 30 minutes.

作者: G.H. Yang Q. Wu J.H. Fu F.Y. Meng

作者单位: Harbin Institute of Technology POBox341,92,Xidazhi Street Harbin, Heilongjiang 150001 CHINA

会议类型: 国际会议

会议名称: 2010 International Conference on Microwave and Millimeter Wave Technology(2010国际微波与毫米波技术会议 ICMMT2010)

会议地点: 成都

会议语种:英文

页码: 1063-1066

在线出版日期: 2010-05-08（万方平台首次上网日期，不代表论文的发表时间）