A Review On The Use Of Soft Computing Methods For Microwave Design Applications

摘要

In this paper, a survey on the use of soft computing methods for microwave design applications is presented. A conceptual overview of four soft computing techniques namely genetic algorithm, neural network, particle swarm optimization, and support vector machine is presented and how these techniques have been used for design applications of microwave domain is reviewed. The review is divided into three major parts: microwave design using evolutionary algorithms, microwave modeling using soft computing, and hybridization of soft computing methods for microwave design. Though efforts have been made to include contribution of all these techniques, the focus is given to cover the review and related work of particle swarm optimization, and support vector machines, as they are relatively new compared to other two techniques which are widely exploited by microwave researchers. The role of these techniques in microwave design tasks, their advantages and drawbacks are described. Finally, the recent trend in using soft computing methods for microwave design is mentioned and some research issues are raised.