Automated Neural-Network-Based Model Generation Algorithms for Microwave Applications

Automated Model Generation (AMG) algorithms are an important technique for creating Artificial Neural Network (ANN) models in microwave design automation. AMG integrates all the subtasks in ANN development into a unified automated algorithm. The assessments of the ANN training phenomena related to under-learning, over-learning and good-learning are automated and the quantitative links between the accuracy of the ANN model, the amount/distribution of training/testing data, and the size of the neural network are established. In this way, the AMG algorithm automatically creates an ANN model with user-desired accuracy, significantly reducing the human time required for modeling. This paper introduces the state of the art in AMG algorithms and its applications in microwave modeling.