An iterative multi-stage algorithm for robust training of RF/microwave neural models

Neural networks recently gained attention as a fast and flexible vehicle to microwave modeling and design. In this paper, we propose an iterative multi-stage (IMS) algorithm to address certain key challenges in neural network based microwave modeling. The IMS decomposes the original complicated microwave behavior into several simpler portions. Each of these simpler portions is modeled separately in a different stage, by training a suitable neural network structure. Neural models from different stages are combined iteratively to produce the overall neural model that represents the original microwave behavior. The proposed technique is demonstrated through examples