REVERSE MODELING OF MICROWAVE CIRCUITS WITH BIDIRECTIONAL NEURAL-NETWORK MODELS

Neural networks have been developed into an alternative modeling appro ach for the microwave circuit-design process. In this paper, we descri be a neural network-based microwave circuit-design approach that imple ments the solution-searching optimization routine by a modified neural network learning process. Both the development of a microwave circuit model and the searching of a design solution can thus take advantage of a hardware neural network processor, which is significantly faster than a software simulation. In addition, a systematic simulation-based approach to convert conventional circuit models into neural network m odels for this design process will be described. The development of a heterojunction bipolar transistor (HBT) amplifier model and its applic ations are demonstrated.