Application of evolutionary algorithm to signal analysis in frequency domain

J. Majewski, R. Wojtyna
{"title":"Application of evolutionary algorithm to signal analysis in frequency domain","authors":"J. Majewski, R. Wojtyna","doi":"10.1109/SPA.2015.7365105","DOIUrl":null,"url":null,"abstract":"In this paper, we consider the problem of creating frequency-domain representation of discrete-time signals with a very small number of samples (several or a dozen). Classical methods of frequency-domain analysis are based on using Discrete Fourier Transform (DFT). However, the DFT method often fails in case of using too small number of samples. One of reasons for that are spectral leakages resulting from convolution of signal spectrum and time window spectrum. The proposed approach to the problem is based on adaptive synthesis which makes it to be deprived of the spectral leakage drawback. To realize the adaptive synthesis idea, using an evolutionary algorithm has been proposed. Superiority of the proposed approach over the Fourier technique is shown on examples. Necessary conditions to achieve good results of our method have also been discussed.","PeriodicalId":423880,"journal":{"name":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPA.2015.7365105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

In this paper, we consider the problem of creating frequency-domain representation of discrete-time signals with a very small number of samples (several or a dozen). Classical methods of frequency-domain analysis are based on using Discrete Fourier Transform (DFT). However, the DFT method often fails in case of using too small number of samples. One of reasons for that are spectral leakages resulting from convolution of signal spectrum and time window spectrum. The proposed approach to the problem is based on adaptive synthesis which makes it to be deprived of the spectral leakage drawback. To realize the adaptive synthesis idea, using an evolutionary algorithm has been proposed. Superiority of the proposed approach over the Fourier technique is shown on examples. Necessary conditions to achieve good results of our method have also been discussed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
进化算法在频域信号分析中的应用
在本文中,我们考虑了用非常少量的样本(几个或十几个)创建离散时间信号的频域表示的问题。经典的频域分析方法是基于离散傅立叶变换(DFT)。然而,由于样本数量过少,DFT方法往往会失败。其原因之一是信号频谱与时窗频谱的卷积导致的频谱泄漏。该方法基于自适应综合,克服了光谱泄漏的缺点。为了实现自适应综合思想,提出了一种进化算法。算例表明了该方法相对于傅里叶方法的优越性。讨论了该方法取得良好效果的必要条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Influence of simultaneous spoken sentences on the properties of spectral peaks Measurements and visualization of sound field distribution around organ pipe Representing the evolving temporal envelope of musical instruments sounds using Computer Vision methods Irregular sampling for X-ray imaging simulation An enhancement of software metrics as failure predictors
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1