Computer aided design of microwave circuits with neural networks

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The objective of the proposed research program is to develop fast and accurate neural models for microwave circuit computer aided design. The emphasis will be on the application of neural network for microwave filter and multiplexer design and simulation.Conventional approaches for microwave filter/ multiplexer modeling are either electromagnetic (EM)-based, which is very accurate but computationally intensive, or empirical or equivalent-circuit-based, which is much faster but limited by the lack of accuracy. As a non-conventional modeling technique, neural networks are originally inspired by the studies of the ability of the human brain to learn from observations and to generalize by abstraction. In recent years, there have been increased interests in applying neural networks to microwave design problems. In this research program, neural modeling is applied to microwave filter and multiplexer design and simulation. Neural models are developed through collecting EM-based simulation data as training data. In the case of output multiplexer application, the frequency range and bandwidth are well defined, making channel filters ideal candidates for neural modeling. After the neural models are trained, modeling of single filters as well as multiplexers can be done hundred of times faster than conventional modeling technique while retaining comparable accuracy.Microwave filters/multiplexers are widely used in space and ground based communications systems. The proposed research program is expected to significantly enhance microwave filter/multiplexer simulation efficiency and product design capabilities due to the superior simulation speed and good accuracy of the developed neural models.