This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 WRI World Congress on Computer Science and Information Engineering
Block Linkage Learning Genetic Algorithm: An Efficient Evolutionary Computational Technique for the Design of Ternary Weighted FIR Filters
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
The representation of genes in a chromosome by locus, value, and block has provided a richer source of relations through representation for a fast converging genetic algorithm. The algorithm circumvents the limitations of linkage learning on the natural selection by injecting the genetic material at high recombination centers, obtained by introducing the fuzziness at the center of acceptance of the genetic material. The evolutionary advantage of propagating the building blocks in the block linkage learning genetic algorithm is used to design a finite impulse response filter with ternary {1,0, -1} weights.
Index Terms:
Genetic Algorithm, Linkage learning
Citation:
B.S. Panwar, Ami Chand, "Block Linkage Learning Genetic Algorithm: An Efficient Evolutionary Computational Technique for the Design of Ternary Weighted FIR Filters," csie, vol. 4, pp.810-814, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
Usage of this product signifies your acceptance of the Terms of Use.