Artificial Neural Network Employed to Design Annular Ring Microstrip Antenna
Neural network computational modules have recently gained as an unconventional and useful tool for RF and microwave modeling and design. Neural network is trained to learn the behavior of Annular Ring MicroStrip Antenna's equivalent circuit parameters. A trained neural network is used for designing fast and less error answers to the task that has to be learned. In this paper, structure of Annular Ring MicroStrip Antenna (ARMSA) is studied and sets of datum are collected for the training of the MultiLayer Perceptron (MLP) Neural Network.