General regression neural network approach to prediction of electric field level in the reverberation chamber
This study presents an approach for the prediction of electric field level which depends on the positions of stirrer and frequency in the mode stirred reverberation chamber. A general regression neural network (GRNN) is used for prediction process. In order to show the system performance, feature selective validation (FSV) technique is given. The simulation results show that the predicted values of electrical field have been obtained with high accuracy. Thus, this technique will facilitate estimation of electric field level in the reverberation chamber which is component of especially mode stirrer reverberation chamber test method.
Citation : Nisanci, M.H., Cengiz, Y., Polat, O., Orlandi, A. and Duffy, A. (2010) General regression neural network approach to prediction of electric field level in the reverberation chamber. Int Journal of Reasoning-based Intelligent Systems, 2 (3/4) pp 168-175
Research Group : Centre for Electronic and Communications Engineering
Research Institute : Institute of Engineering Sciences (IES)