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Support vector design of the microstrip lines

✍ Scribed by Filiz Güneş; Nurhan Türker Tokan; Fikret Gürgen

Publisher
John Wiley and Sons
Year
2008
Tongue
English
Weight
568 KB
Volume
18
Category
Article
ISSN
1096-4290

No coin nor oath required. For personal study only.

✦ Synopsis

In this article, the support vector regression is adapted to the analysis and synthesis of microstrip lines on all isotropic/anisotropic dielectric materials, which is a novel technique based on the rigorous mathematical fundamentals and the most competitive technique to the popular artificial neural networks (ANN). In this design process, accuracy, computational efficiency and number of support vectors are investigated in detail and the support vector regression performance is compared with an ANN performance. It can be concluded that the ANN may be replaced by the support vector machines in the regression applications because of its higher approximation capability and much faster convergence rate with the sparse solution technique. Synthesis is achieved by utilizing the analysis blackbox bidirectionally by reverse training. Furthermore, by using the adaptive step size, a much faster convergence rate is obtained in the reverse training. Besides, design of microstrip lines on the most commonly used isotropic/anisotropic dielectric materials are given as the worked examples. V

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