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Microstrip filter design using FDTD and neural networks
Author(s) -
Banciu M. G.,
Ambikairajah E.,
Ramer R.
Publication year - 2002
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.10422
Subject(s) - finite difference time domain method , microstrip , artificial neural network , microwave , electronic engineering , computation , filter (signal processing) , engineering , computer science , algorithm , telecommunications , electrical engineering , artificial intelligence , physics , optics
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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