DocumentCode
2705686
Title
Output prediction about crosstalk coupling of representative multi-cable bundle on aircraft platform based on neural network
Author
Dai, Jian ; Dai, Fei ; Zhao, Xiaoying
Author_Institution
Sch. of Electron. & Inf. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
fYear
2009
fDate
27-29 Oct. 2009
Firstpage
381
Lastpage
384
Abstract
A method of output prediction about crosstalk coupling of multi-cable bundle on aircraft is presented without solving the coupling matrix. BP neural network is used to simulate the coupling relation between input and output. The network of input and output are trained with LMBP algorithm. MOM is applied to calculate the output value of multi-cable bundle when inputs in different frequency point are given through establishing 3D model of transmission lines. It´s shown that the predicted values of neural network in different frequency points coincide with values of MOM simulative outputs well. Otherwise a concept of relative coupling error is put forward to estimating the accuracy of prediction algorithm. The predicted values are much closer to the simulative ones after the inputs of neural network have been optimized properly. This method can be used to predict the output of nonlinear multi-cables coupling in complex system structure.
Keywords
aircraft; backpropagation; computational electromagnetics; electromagnetic coupling; electromagnetic interference; neural nets; BP neural network; LMBP algorithm; MOM; aircraft; complex system structure; crosstalk coupling; multi-cable bundle; nonlinear multi-cables coupling; output prediction; Accuracy; Aircraft; Couplings; Crosstalk; Frequency; Message-oriented middleware; Neural networks; Prediction algorithms; Predictive models; Transmission line matrix methods; coupling; crosstalk; multi-cable; neural network; prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2009 3rd IEEE International Symposium on
Conference_Location
Beijing
Print_ISBN
978-1-4244-4076-4
Type
conf
DOI
10.1109/MAPE.2009.5355734
Filename
5355734
Link To Document