{"title":"New variable mode QRD adaptive filtering algorithm for acoustic echo cancellation","authors":"Cheng Lu, Ruitang Mao, Yongqiang Zhang, Yi Zhou","doi":"10.1109/ICEDIF.2015.7280151","DOIUrl":null,"url":null,"abstract":"This paper studies a new switch QR decomposition adaptive filtering algorithm for acoustic echo cancellation (AEC). Based on the flexible p-TA-QR-LS algorithm, the proposed algorithm employs an efficient switching scheme based on voice activity detection and linear prediction, which enables it to distinguish the significant and insignificant input speech periods. The resultant variable mode p-TA-QR-LS algorithm can work with two switching modes (p=1 and N) and is thus suitable for AEC problem where the needs for convergence enhancement and for computational complexity reduction can be balanced.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEDIF.2015.7280151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies a new switch QR decomposition adaptive filtering algorithm for acoustic echo cancellation (AEC). Based on the flexible p-TA-QR-LS algorithm, the proposed algorithm employs an efficient switching scheme based on voice activity detection and linear prediction, which enables it to distinguish the significant and insignificant input speech periods. The resultant variable mode p-TA-QR-LS algorithm can work with two switching modes (p=1 and N) and is thus suitable for AEC problem where the needs for convergence enhancement and for computational complexity reduction can be balanced.
研究了一种用于声回波消除的开关QR分解自适应滤波算法。该算法在灵活的p-TA-QR-LS算法的基础上,采用基于语音活动检测和线性预测的高效切换方案,能够区分重要和不重要的输入语音周期。由此得到的变模p- ta - qr - ls算法可以在两种切换模式(p=1和N)下工作,因此适合于兼顾收敛性增强和计算复杂度降低的AEC问题。