By Topic

Fitness Evaluation Expansion to Enhance GA'S Performance in Evolvable Hardware

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

4 Author(s)
Benkhelifa, E. ; Bristol Robot. Lab., Univ. of the West of England, Bristol ; Pipe, A. ; Nibouche, M. ; Dragffy, G.

In this paper the authors introduce a novel experimental method when using genetic algorithms (GAs) to design and optimise digital hardware (HW). This approach proved to enhance the GA's performance. It produced more design solutions than selected comparable techniques used by others and maximises optimisation. The novel aspect of our algorithm works at the fitness evaluation stage, where every single unit's output in the evolved array is taken as a potential solution, instead of specifying specific cells for desired outputs. This will be referred to in this paper as fitness evaluation expansion (FEE). The FEE approach isevaluated experimentally by evolving a 2bit Multiplier and 2bit binary Adder.

Published in:

Adaptive Hardware and Systems, 2008. AHS '08. NASA/ESA Conference on

Date of Conference:

22-25 June 2008