Artificial Neural Networks Modeling Technology for Substrate Integrated Suspended Line

A new method for parameter modeling of self-packaged Substrate Integrated Suspended Line (SISL) devices based on artificial neural network is proposed. The method only uses the input and output signals of self-packaged SISL devices, and does not need to establish the internal structure information of the model. The cost of modeling is greatly reduced and the design cycle of microwave passive devices is shortened. In addition, an improved training method is proposed based on the neural network to learn the relationship between electromagnetic response and geometric parameters, so that the proposed model can efficiently and accurately match the characteristics of SISL devices. The model takes geometric parameters as variables. It can provide the exact and rapid prediction for the electromagnetic response of SISL devices. The validity and accuracy of the parameter modeling technique based on an artificial neural network are verified by a modeling example of a wideband Yagi antenna.