Knowledge-based neural network approach for microwave modeling and design

This thesis presents the use of knowledge-based neural networks for microwave circuit modeling and design. A general method combining microwave empirical/equivalent model with artificial neural network is proposed. This method, called generalized knowledge-based neural network (GKBNN), unifies several existing methods and provides increased model accuracy and extrapolation capability, even if the training data is limited. The method also provides a systematic approach to efficiently handle a wider variety of modeling cases than the several existing knowledge based methods combined. It is applied to microwave device and transmission line modeling for high frequency/high speed circuit design.; The topic of knowledge based neural modeling for nonlinear microwave devices is pioneered for the first time in this thesis. Two methods, dynamic neural modeling utilizing difference method and neuro-space mapping applying space mapping concept, are proposed here. (Abstract shortened by UMI.)...