Design optimization of loop antenna using Competitive Learning ANN

Out of several antenna design techniques the Artificial Neural Network (ANN) based method is suitable for prediction of characteristic parameters of loop antenna by considering transmit - receive conditions of practical communication set-ups. The predicted set of parameters can be used to fix dimensions of a loop antenna which involves theoretical calculations. This work proposes an approach to determine the best suitable combination of conductor thickness and loop radius using Competitive Learning ANN from predicted values of antenna parameters. The proposed method uses the ANN predicted parameters to find the optimized set of conductor thickness and loop radius using Self Organizing Map (SOM) to fix the layout of a loop antenna for applications with electrically driven finite element grids.