Neural Based EM Modeling

This paper reviews state-of-the art neural network (NN) modeling techniques for electromagnetic (EM) modeling. We describe the advantages of neural network models in terms of speed and accuracy. Conventional simulator based EM models are time consuming. An iterative evaluation of these models is used for the design parameters, which are CPU intensive. Neural network model can provide fast and accurate models for electromagnetic devices. Time domain EM modeling is also presented here using recurrent neural network (RNN) technique. The trained RNN model can be used in the circuit simulators for circuit analysis. Examples of neural network based EM models are also presented which proves that neural network base models are both fast and accurate and thus efficient for EM based design.