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Application of support vector machines to the antenna design
Author(s) -
Zheng Z.,
Chen X.,
Huang K.
Publication year - 2011
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.20491
Subject(s) - support vector machine , antenna (radio) , computer science , generalization , structural risk minimization , patch antenna , electronic engineering , minification , computer engineering , machine learning , engineering , telecommunications , mathematics , world wide web , mathematical analysis
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.