Solving The Inverse Problem Of Microwave Field Based On The Artificial Neural Network

For the sake of large computation and great complexity of using conventional approach to solve the inverse problem of microwave electromagnetic field, in this paper, we will apply artificial neural network to solve this kind of inverse problem. Due to the non-linear nature of the artificial and parallel treatment on data, the resolution of the microwave electromagnetic field inverse problem can be made without calculation models but only with the simple couple data about their microwave field system, the model can be simulated by the self-study of the network. Moreover, thanks to the robust character and resistant bothered capacity of the network, the result will not be bothered even if there are some mistakes in data. The above feathers of the artificial neural network will offer a broad future in the application of the microwave electromagnetic field inverse problem.To obtain the accurate data which it is used to train the artificial neural network, we apply the analytical solution approach basing on the operation's Eigenfunction to solve the computation of the microwave electromagnetic. During the training process, we will have the Conjugate gradient to train artificial neural network and select the learning rate by our way to ensure the validation of training algorithm.In the paper, we will check up the inverse problem solution which is obtained by the way of artificial neural network by some numerical experiment, by the experiment result, we can include that solving the inverse problem of microwave problem basing on the artificial neural network is more accurate than the traditional approach.