Artificial neural network models for coaxial to waveguide adapters

Artificial neural networks provide fast and accurate models for the modelin g, simulation, and optimization of microwave and millimeter wave components . In this paper, a multilayer perceptron neural network (MLPNN) is used to model a millimeter wave coaxial to waveguide adapter. The MLPNN is electrom agnetically developed with a set of training data that are produced by the full-wave finite-difference time-domain (FDTD) method. One type of the desi gns of experiments, the central composite technique, is used to allow for a minimum number of FDTD simulations that is needed to be performed. The MLP NN models are useful for the CAD of wideband coaxial to waveguide adapter.