DocumentCode
508478
Title
Adaptive genetic algorithm for optimal selection of non-uniform code based on Euclidean distance
Author
Zhang Mingbo ; Luo Feng ; Wu Shunjun
Author_Institution
Nat. Key Lab. of Radar Signal Process., Xidian Univ., Xi´an
fYear
2009
fDate
20-22 April 2009
Firstpage
1
Lastpage
4
Abstract
A novel adaptive genetic algorithm based on Euclidean distance (EAGA) is presented. This algorithm can strengthen and preserve the diversity of population. Meanwhile some improvements are implemented to prevent degeneration during the optimization process by introducing new individuals generated by certain rules into the group. Compared with the other three algorithms, EAGA shows an effective global search capacity.
Keywords
genetic algorithms; radar signal processing; signal sampling; Euclidean distance; adaptive genetic algorithm; global search capacity; non-uniform code; radar signal sampling; staggered code; Euclidean distance; adaptive control; genetic algorithm; staggered code;
fLanguage
English
Publisher
iet
Conference_Titel
Radar Conference, 2009 IET International
Conference_Location
Guilin
ISSN
0537-9989
Print_ISBN
978-1-84919-010-7
Type
conf
Filename
5367340
Link To Document