Date of Award
Summer 1994
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Arkadan, Abdul-Rahman A.
Second Advisor
Belfore, Lee A.
Third Advisor
Josse, Fabien J.
Abstract
The inverse problems in electromagnetic system design, optimization, and identification received lately much more attention and interest. The inverse electromagnetic field problem can be stated as the problem of predicting the values of the descriptive parameters of a device or system, which produces the required or given performance. The prediction, in general, can be tackled as a system mapping problem. Artificial Neural Network is a powerful tool in pattern recognition and system mapping, and Finite Element Analysis is widely used for solving electromagnetic field problems. In this thesis, The Artificial Neural Networks is investigated and applied in conjunction with Finite Element Analysis to the solution of the inverse electromagnetic field problem. The purpose of this approach is to exploit the recognition and mapping capabilities of neural networks and the analytical strength of Finite Element method.
Recommended Citation
Chen, Yue, "Artificial Neural Networks for the Inverse Electromagnetic Field Problem" (1994). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4051.
https://epublications.marquette.edu/theses/4051