Support Vector Characterisation of the Microstrip Antennas Based on Measurements

In this work, Support Vector Machine (SVM) formulation is worked out based upon L measured data for the resonant frequency, operation bandwidth, input impedance of a rectangular microstrip antenna. Results of the formulation are compared with the theoretical results obtained in literature, much better characterization is observed with greater accuracy. At the same time, Artificial Neural Network (ANN) is employed in generalization of the data on the resonant frequency, operation bandwidth, and input impedance of the antenna. Performances of the two advanced nonlinear learning machines are compared and superiority of the SVM is verified.