The main focus of this paper is to describe a developed and dynamic method of designing finite impulse response filters with automatic, rapid and less computational complexity by an efficient Genetic approach. To obtain such efficiency, specific filter coefficient coding scheme has been studied and implemented. The algorithm generates a population of genomes that represents the filter coefficient where new genomes are generated by crossover, mutation operations methods. Our proposed genetic technique has able to give better result compare to other method
%0 Journal Article
%1 IJACSA.2010.010614
%A Ajoy Kumar Dey Avijit Saha, Shibani Ghosh
%D 2010
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Algorithm; FIR: Genetic design; filter network. neural optimization;
%N 6
%T A Method of Genetic Algorithm (GA) for FIR Filter Construction: Design and Development with Newer Approaches in Neural Network Platform
%U http://ijacsa.thesai.org/
%V 1
%X The main focus of this paper is to describe a developed and dynamic method of designing finite impulse response filters with automatic, rapid and less computational complexity by an efficient Genetic approach. To obtain such efficiency, specific filter coefficient coding scheme has been studied and implemented. The algorithm generates a population of genomes that represents the filter coefficient where new genomes are generated by crossover, mutation operations methods. Our proposed genetic technique has able to give better result compare to other method
@article{IJACSA.2010.010614,
abstract = {The main focus of this paper is to describe a developed and dynamic method of designing finite impulse response filters with automatic, rapid and less computational complexity by an efficient Genetic approach. To obtain such efficiency, specific filter coefficient coding scheme has been studied and implemented. The algorithm generates a population of genomes that represents the filter coefficient where new genomes are generated by crossover, mutation operations methods. Our proposed genetic technique has able to give better result compare to other method},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Ajoy Kumar Dey Avijit Saha}, Shibani Ghosh},
biburl = {https://www.bibsonomy.org/bibtex/2b7b21f67ba497e8c41102888516f1651/thesaiorg},
interhash = {05fa88d4be950abab148d4523e0d9ab6},
intrahash = {b7b21f67ba497e8c41102888516f1651},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Algorithm; FIR: Genetic design; filter network. neural optimization;},
number = 6,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{A Method of Genetic Algorithm (GA) for FIR Filter Construction: Design and Development with Newer Approaches in Neural Network Platform}},
url = {http://ijacsa.thesai.org/},
volume = 1,
year = 2010
}