Reconfigurable Microstrip Antenna Optimization Through Artificial Neural Networks

摘要: Artificial neural networks are applied to reconfigurable microstrip antenna design and optimization in this paper. The change of resistor value leads two different results, exploited as the less high-performance models align them a solution through artificial networks. Two phases employed by (I) using multilayer perceptron, (II) prior knowledge input methods. techniques implemented Matlab. In proposed example, S-parameter is optimized separate processes. resonates initially at dual-band between 1–5 GHz. modified adding control circuit included separately resistors switches both conductor parts. By increasing decrease return loss optimal operating frequencies observed.