Intelligent model of microwave low-pass filter using PDGS with defected rectangles

Microwave low-pass filter (LPF) is the kind of device which can separate different signals within microwave frequency range, widely used in microwave communication system. Periodic defected ground structures (PDGS) with defected rectangles has excellent low-pass properties when periodic unit amounts and structure sizes meet definite conditions. In this paper, intelligent model of PDGS-LPF with etched rectangles is developed for the first time on the basis of FDTD analysis. Periodic unit amounts, the structure sizes of PDGS and the frequency are defined as the input samples of the model, and the parameters of transmission coefficient (S21) are defined as the output samples according to artificial neural network (ANN) theory. Transmission coefficient of PDGS at any arbitrary periodic unit amounts, any arbitrary structure sizes and any arbitrary frequency within training values range can be obtained quickly from intelligent model after the ANN has been successfully trained with the Bayesian Regularization algorithm. Finally, intelligent model has been approved by FDTD results. It is also showed that intelligent model is very effective, which will provide powerful approach for the precise analysis and quick design of microwave low-pass filter using PDGS with defected rectangles.