Neurocomputational Approach for Feed-Position Estimation in Circular Micro-strip Antenna

This paper presents a neurocomputational model for estimation of feed-position in circular microstrip antenna. The difficulty in computing the feed position in circular microstrip antenna lies due to the involvement of a large number of physical parameters including their associated optimal values. It is indeed very difficult to formulate an exact numerical solution merely on practical observations based empirical studies. In order to circumvent this problem, an alternative solution is achieved using neurocomputational model. The proposed technique used feed-forward back-propagation artificial neural network (FFBP-ANN) trained with Levenberg-Marquardt algorithm. The results of neural estimation are quite promising.