Neural Network Models for Finline Discontinuities

Authors: Jin Long¹; Ruan Cheng-Li²

Source: International Journal of Infrared and Millimeter Waves, Volume 25, Number 12, December 2004 , pp. 1819-1827(9)

Publisher: Springer

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Abstract:

The radial basis network is used as the finline discontinuities electromagnetic artifical neural network(EM-ANN) models. EM software analysis is employed to characterize finline discontinuities. EM-ANN models are then trained using physical parameters and frequency as inputs and equivalent electric circuit element parameters of finline discontinuities as outputs. Once trained , the EM-ANN models can simulate equivalent electric circuit element parameters of finline step, notch and strip very fast and efficiently.

Keywords: millimeterwave transmission line; finline discontinuity; radial basis function; EM-ANN

Document Type: Research article

DOI: http://dx.doi.org/10.1007/s10762-004-0203-1

Affiliations: 1: College of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054, People’s Republic of China; , Email: jinlong@people.com.cn 2: College of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054, People’s Republic of China,

Publication date: 2004-12-01