Citation
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
Abstract
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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Official URL or Download Paper: http://www.ajbasweb.com/old/Ajbas_september_2010.h...
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Engineering |
| Publisher: | American-Eurasian Network for Scientific Information |
| Keywords: | FFT processor; Signal to noise ratio; Switching activity |
| Depositing User: | Nabilah Mustapa |
| Date Deposited: | 08 May 2019 07:27 |
| Last Modified: | 08 May 2019 07:27 |
| URI: | http://psasir.upm.edu.my/id/eprint/14872 |
| Statistic Details: | View Download Statistic |
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