Microwave Devices and Antennas Modelling by Support Vector Regression Machines

Development of fast and accurate models of microwave devices and antennas is of paramount importance in computer-aided design and circuit analysis. At this purpose, artificial neural networks (ANNs) have been extensively exploited in technical literature. However, in the last years support vector machines (SVMs) developed by Vapnik are gaining popularity due to many attractive features capable to overcome the limitations connected to ANNs. In this work, support vector regression machines (SVRMs) modelling performances are investigated and compared with ANNs performances by means of several cases of study.