Applications of artificial neural network techniques in microwave filter modeling, optimization and design

This paper reviews state-of-the-art microwave filter modeling, optimization and design methods using artificial neural network (ANN) technique. Innovative methodologies of using ANN in microwave filter analysis and synthesis are discussed. Various ANN structures including wavelet and radial basis function have been utilized for this purpose. ANN also finds application in filter yield prediction and optimization. The results from different work demonstrate that ANN technique can reduce the cost of computation significantly and thus can produce fast and accurate result compared to the conventional electromagnetic (EM) methods.