Adaptive neuro-fuzzy inference system for the computation of the bandwidth of electrically thin and thick rectangular microstrip antennas

A new method based on the adaptive neuro-fuzzy inference system (ANFIS) for calculating the bandwidth of the rectangular microstrip antennas with thin and thick substrates is presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. It combines the powerful features of fuzzy inference systems with those of neural networks to achieve a desired performance. A hybrid learning algorithm based on the least square method and the backpropagation algorithm is used to identify the parameters of ANFIS. The bandwidth results obtained by using ANFIS are in excellent agreement with the experimental results available in the literature