Neural Model of the Slotted Circular Microstrip Patch Antenna

In this paper, a neural model of a slotted circular patch microstrip antenna is proposed to determine the first and second resonant frequencies and decide whether the antenna is matched when it radiates at these frequencies. The input parameters of the neural model are the antenna radius and the dimensions of the slot with respect to the radius. The presented model is based on a combination of a multilayer perceptron network (MLP) and a radial basis function (RBF) network. The accuracy of the proposed neural model is investigated.