A control strategy for electromagnetic near and far field calculation

The ability of neural networks to predict the electromagnetic field of one dimensional sources as well as of two- and three dimensional sources in a wide dynamic range with small error is an imperative condition for use of neural networks in the analysis of complex and fast printed circuit boards. As presented in this paper, Sigma-Pi networks are able to achieve this condition. Because of the high dynamic of the input and the output data within the region of investigation, a wry fast back propagation learning algorithm is used to train the neural network and also presented in this paper. Finally, a short outlook is given to the use of neural networks in analysis of printed circuit boards.