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The antenna design is a complicated and time-consuming procedure. This work explores using support vector machines (SVMs), a statistical learning theory based on the structural risk minimization principle and has a great generalization capability, as a fast and accurate tool in the antenna design. As examples, SVMs is used to design a rectangular patch antenna and a rectangular patch antenna array. Results show, after an appropriate training, SVMs is able to effectively design antennas with high accuracy. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.
Zheng et al. (Mon,) studied this question.
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