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/
http://psasir.upm.edu.my/id/eprint/14872/1/Genetic%20algorithm%20optimization%20for%20coefficient%20of%20FFT%20processor.pdf
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author Pang, Jia Hong
Sulaiman, Nasri
author_facet Pang, Jia Hong
Sulaiman, Nasri
author_sort Pang, Jia Hong
building UPM Institutional Repository
collection Online Access
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.
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institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T08:00:25Z
publishDate 2010
publisher American-Eurasian Network for Scientific Information
recordtype eprints
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spelling upm-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
spellingShingle Pang, Jia Hong
Sulaiman, Nasri
Genetic algorithm optimization for coefficient of FFT processor
title 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_short Genetic algorithm optimization for coefficient of FFT processor
title_sort genetic algorithm optimization for coefficient of fft processor
url http://psasir.upm.edu.my/id/eprint/14872/
http://psasir.upm.edu.my/id/eprint/14872/
http://psasir.upm.edu.my/id/eprint/14872/1/Genetic%20algorithm%20optimization%20for%20coefficient%20of%20FFT%20processor.pdf