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Microstrip filter design using FDTD and neural networks

✍ Scribed by M. G. Banciu; E. Ambikairajah; R. Ramer

Publisher: John Wiley and Sons
Year: 2002
Tongue: English
Weight: 226 KB
Volume: 34
Category: Article
ISSN: 0895-2477
DOI: 10.1002/mop.10422

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

A new design technique using the FDTD method and neural networks is applied to a microstrip filter. The total design time is reduced by two means. First, an iterative ARMA signal estimation technique is utilized to reduce the computation time for each FDTD run. Second, the number of FDTD simulations is decreased with the use of the device model provided by a neural network with the ARMA coefficients at the output. The trained network was then incorporated to an optimization procedure for a microstrip filter design. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 34: 219–224, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10422

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Figure 6 Measured axial ratio in the broadside direction against frequency for the proposed antenna in Figure 5 with left-hand CP Ž . radiation feed at point A ; h s 1.6 mm, s 4.4, L s 30 mm, r Ž . Ž . Ž . S s 6.4 mm 4.7 ⍀ , 5.0 mm 0 ⍀ , d s 11.2 mm 4.7 ⍀ , 12.2 mm Ž . 0 ⍀ TABLE 2 Characteristics of