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Genetic algorithm optimization for coefficient of FFT processor

This paper describes the implementation of Single-objective Genetic Algorithm (SOGA) and Multi-objectives Genetic Algorithm (MOGA) to optimize the pipelined Fast Fourier Transform (FFT) coefficient in order to improve the performance of Signal to Noise Ratio (SNR) and also the Switching Activity (SA...

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Main Authors: Pang, Jia Hong, Sulaiman, Nasri
Format: Article
Language:English
Published: American-Eurasian Network for Scientific Information 2010
Online Access:http://psasir.upm.edu.my/id/eprint/14872/1/Genetic%20algorithm%20optimization%20for%20coefficient%20of%20FFT%20processor.pdf
http://psasir.upm.edu.my/id/eprint/14872/
http://www.ajbasweb.com/old/Ajbas_september_2010.html
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spelling my.upm.eprints.148722019-05-08T07:27:19Z http://psasir.upm.edu.my/id/eprint/14872/ Genetic algorithm optimization for coefficient of FFT processor Pang, Jia Hong Sulaiman, Nasri This paper describes the implementation of Single-objective Genetic Algorithm (SOGA) and Multi-objectives Genetic Algorithm (MOGA) to optimize the pipelined Fast Fourier Transform (FFT) coefficient in order to improve the performance of Signal to Noise Ratio (SNR) and also the Switching Activity (SA). The SA and SNR are optimized separately in a Radix-4 Single Path Delay Feedback (R4SDF) pipelined Fast Fourier Transform (FFT) processor using SOGA. The MOGA optimized both objectives using Weighted-Sum approach. American-Eurasian Network for Scientific Information 2010 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/14872/1/Genetic%20algorithm%20optimization%20for%20coefficient%20of%20FFT%20processor.pdf Pang, Jia Hong and Sulaiman, Nasri (2010) Genetic algorithm optimization for coefficient of FFT processor. Australian Journal of Basic and Applied Sciences, 4 (9). pp. 4184-4192. ISSN 1991-8178 http://www.ajbasweb.com/old/Ajbas_september_2010.html
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper describes the implementation of Single-objective Genetic Algorithm (SOGA) and Multi-objectives Genetic Algorithm (MOGA) to optimize the pipelined Fast Fourier Transform (FFT) coefficient in order to improve the performance of Signal to Noise Ratio (SNR) and also the Switching Activity (SA). The SA and SNR are optimized separately in a Radix-4 Single Path Delay Feedback (R4SDF) pipelined Fast Fourier Transform (FFT) processor using SOGA. The MOGA optimized both objectives using Weighted-Sum approach.
format Article
author Pang, Jia Hong
Sulaiman, Nasri
spellingShingle Pang, Jia Hong
Sulaiman, Nasri
Genetic algorithm optimization for coefficient of FFT processor
author_facet Pang, Jia Hong
Sulaiman, Nasri
author_sort Pang, Jia Hong
title Genetic algorithm optimization for coefficient of FFT processor
title_short Genetic algorithm optimization for coefficient of FFT processor
title_full Genetic algorithm optimization for coefficient of FFT processor
title_fullStr Genetic algorithm optimization for coefficient of FFT processor
title_full_unstemmed Genetic algorithm optimization for coefficient of FFT processor
title_sort genetic algorithm optimization for coefficient of fft processor
publisher American-Eurasian Network for Scientific Information
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/14872/1/Genetic%20algorithm%20optimization%20for%20coefficient%20of%20FFT%20processor.pdf
http://psasir.upm.edu.my/id/eprint/14872/
http://www.ajbasweb.com/old/Ajbas_september_2010.html
_version_ 1643825764763697152
score 13.251813

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