{"title":"Stability of Residual Acoustic Noise Variance in active control of stochastic noise","authors":"Iman Tabatabaei Ardekani, W. Abdulla","doi":"10.1109/ICASSP.2013.6637673","DOIUrl":null,"url":null,"abstract":"This paper concerns about the theoretical stability of the adaptation process performed by the Filtered-x Least Mean Square (FxLMS) algorithm in active control of acoustic noise. A dynamic model for the Variance of Residual Acoustic Noise (VRAN) is developed and it is shown that the stability of this model is a sufficient condition for the stability of the adaptation process. The basic rules governing the VRAN root locus are developed, based on which an upper-bound for the adaptation step-size is derived. This upper-bound can apply to a general case with an arbitrary secondary path, unlike the traditional upper-bound used in adaptive filter theory, which was derived only for pure delay secondary paths.","PeriodicalId":183968,"journal":{"name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2013.6637673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper concerns about the theoretical stability of the adaptation process performed by the Filtered-x Least Mean Square (FxLMS) algorithm in active control of acoustic noise. A dynamic model for the Variance of Residual Acoustic Noise (VRAN) is developed and it is shown that the stability of this model is a sufficient condition for the stability of the adaptation process. The basic rules governing the VRAN root locus are developed, based on which an upper-bound for the adaptation step-size is derived. This upper-bound can apply to a general case with an arbitrary secondary path, unlike the traditional upper-bound used in adaptive filter theory, which was derived only for pure delay secondary paths.
本文研究了滤波-x最小均方(filter -x Least Mean Square, FxLMS)算法在噪声主动控制中的自适应过程的理论稳定性。建立了残馀噪声方差(VRAN)的动态模型,并证明了该模型的稳定性是自适应过程稳定的充分条件。建立了控制VRAN根轨迹的基本规则,并在此基础上导出了自适应步长的上界。该上界适用于具有任意副路径的一般情况,而不像传统的自适应滤波理论中所使用的上界只适用于纯延迟副路径。