一种复杂自适应谐波IIR陷波滤波器

Li Tan, Haiyan Zhang, Jean Jiang
{"title":"一种复杂自适应谐波IIR陷波滤波器","authors":"Li Tan, Haiyan Zhang, Jean Jiang","doi":"10.1109/EIT.2015.7293327","DOIUrl":null,"url":null,"abstract":"A complex adaptive Harmonic IIR notch filter is proposed for estimating and tracking the frequency of periodic complex signals in a noisy harmonic environment. The transfer function of the developed notch filter consists of cascaded first-order complex transfer functions whose notch frequencies are constrained to the fundamental and harmonic frequencies. The least mean squares (LMS) algorithm is developed and a formula to determine the stability bound for the algorithm is derived. In addition, an improved simple scheme is devised to prevent the adaptive algorithm from converging to its local minima of the mean square error (MSE) function when the tracked signal fundamental frequency changes. Computer simulations validate the performance of the developed algorithm.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A complex adaptive Harmonic IIR notch filter\",\"authors\":\"Li Tan, Haiyan Zhang, Jean Jiang\",\"doi\":\"10.1109/EIT.2015.7293327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A complex adaptive Harmonic IIR notch filter is proposed for estimating and tracking the frequency of periodic complex signals in a noisy harmonic environment. The transfer function of the developed notch filter consists of cascaded first-order complex transfer functions whose notch frequencies are constrained to the fundamental and harmonic frequencies. The least mean squares (LMS) algorithm is developed and a formula to determine the stability bound for the algorithm is derived. In addition, an improved simple scheme is devised to prevent the adaptive algorithm from converging to its local minima of the mean square error (MSE) function when the tracked signal fundamental frequency changes. Computer simulations validate the performance of the developed algorithm.\",\"PeriodicalId\":415614,\"journal\":{\"name\":\"2015 IEEE International Conference on Electro/Information Technology (EIT)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Electro/Information Technology (EIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIT.2015.7293327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Electro/Information Technology (EIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2015.7293327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

提出了一种复杂自适应谐波陷波滤波器,用于噪声谐波环境下周期性复杂信号的频率估计和跟踪。所开发的陷波滤波器的传递函数由级联的一阶复传递函数组成,其陷波频率被限制为基频和谐波频率。提出了最小均方算法,并推导了确定该算法稳定性界的公式。此外,设计了一种改进的简单方案,防止自适应算法在跟踪信号基频变化时收敛到均方误差(MSE)函数的局部最小值。计算机仿真验证了所开发算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A complex adaptive Harmonic IIR notch filter
A complex adaptive Harmonic IIR notch filter is proposed for estimating and tracking the frequency of periodic complex signals in a noisy harmonic environment. The transfer function of the developed notch filter consists of cascaded first-order complex transfer functions whose notch frequencies are constrained to the fundamental and harmonic frequencies. The least mean squares (LMS) algorithm is developed and a formula to determine the stability bound for the algorithm is derived. In addition, an improved simple scheme is devised to prevent the adaptive algorithm from converging to its local minima of the mean square error (MSE) function when the tracked signal fundamental frequency changes. Computer simulations validate the performance of the developed algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信