Cart (Loading....) | Create Account
Close category search window
 

Parallel GA-based approach for microwave imaging applications

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
$31 $13
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

6 Author(s)
Massa, A. ; Dept. of Inf. & Commun. Technol., Univ. of Trento, Italy ; Franceschini, D. ; Franceschini, G. ; Pastorino, M.
more authors

Genetic algorithms (GAs) are well-known optimization strategies able to deal with nonlinear functions as those arising in inverse scattering problems. However, they are computationally expensive, thus offering poor performances in terms of general efficiency when compared with inversion techniques based on deterministic optimization methods. In this paper, a parallel implementation of an inverse scattering procedure based on a suitable hybrid genetic algorithm is presented. The proposed strategy is aimed at reducing the overall clock time in order to make the approach competitive with gradient-based methods in terms of runtime, but preserving the capabilities of escaping from local minima. This result is achieved by exploiting the natural parallelism of evolutionary techniques and the searching capabilities of the hybrid approach . The effectiveness of the proposed implementation is demonstrated by considering a selected numerical benchmark related to two-dimensional scattering geometries.

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:53 ,  Issue: 10 )

Date of Publication:

Oct. 2005

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.