By Topic

Genetic algorithm based inversion of neural networks applied to optimised design of UWB planar antennas

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
D. O. Vasylenko ; Ruhr-Univ. of Bochum, Bochum ; P. Edenhofer ; F. F. Dubrovka

An inversion of artificial neural networks using a genetic algorithm is presented for a novel concept of optimisation applied to UWB planar antennas of bow-tie type with respect to specified values of antenna performance in the frequency range 3.1-10.6 GHz. This efficient concept is shown to achieve significant reduction in computing time for optimisation. The multidimensional inversion is characterised by a simple composite fitness or target function that includes antenna parameters as a function of signal frequency or/and angle dependence. Good impedance matching and gain performance is achieved over the whole frequency range by adequately modifying the radiating contour profile of the conventional triangular bow-tie antenna.

Published in:

Electronics Letters  (Volume:44 ,  Issue: 3 )