DocumentCode :
2251475
Title :
Genetic Programming for the CNN-UM
Author :
Pazienza, Giovanni Egidio ; Gomez-Ramirez, E. ; Vilasís-Cardona, Xavier
Author_Institution :
Departament d´´Electronica, Univ. Ramon Llull, Barcelona
fYear :
2006
fDate :
28-30 Aug. 2006
Firstpage :
1
Lastpage :
6
Abstract :
We work on automatic tools - based on evolutionary techniques - to generate analogic algorithms and for image processing. The main improvements with respect to previous similar approaches regard the fitness function, and the way in which the template set for the GP algorithm is chosen. Our approach is successfully tested for different problems
Keywords :
cellular neural nets; genetic algorithms; image processing; CNN-UM; analogic algorithms; evolutionary techniques; fitness function; genetic programming; image processing; multitemplate programs; weighted Hamming distance; Algorithm design and analysis; Cellular neural networks; Electronic mail; Evolutionary computation; Genetic programming; Hamming distance; Image processing; Libraries; Topology; Turing machines; Analogic algorithms; genetic programming; multi-template programs; weighted Hamming distance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications, 2006. CNNA '06. 10th International Workshop on
Conference_Location :
Istanbul
Print_ISBN :
1-4244-0639-0
Electronic_ISBN :
1-4244-0640-4
Type :
conf
DOI :
10.1109/CNNA.2006.341616
Filename :
4145856
Link To Document :
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