Title :
Artificial neural network for the inverse electromagnetic problem of system identification
Author :
Arkadan, A.A. ; Chen, Y.
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
Abstract :
An approach which is based on the use of artificial neural networks and finite element analysis is used to solve the inverse problem of system identification. The approach is used on a test problem to identify location, material and values of unknown sources within an inaccessible region. A comparison of actual and predicted values of the unknown parameters demonstrates the validity of this approach
Keywords :
backpropagation; electrical engineering computing; electromagnetic devices; finite element analysis; identification; inverse problems; neural nets; artificial neural networks; backpropagation learning algorithm; finite element analysis; inverse electromagnetic problem; location identification; material identification; system identification; Artificial neural networks; Computational electromagnetics; Computer networks; Design optimization; Electromagnetic measurements; Electrostatic analysis; Finite element methods; Inverse problems; Materials testing; System identification;
Conference_Titel :
Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE
Conference_Location :
Miami, FL
Print_ISBN :
0-7803-1797-1
DOI :
10.1109/SECON.1994.324289
