.png){kind=icon}
返回
Delayed-X LMS algorithm: An efficient ANC algorithm utilizing robustness of cancellation path model
.png){kind=icon}
PRE
AI
DOI：10.1006/jsvi.1997.1484.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In conventional ANC (Active Noise Control), the cancellation path is usually modelled by a FIR filter with many coefficients. In this study, a Delayed-X LMS algorithm is investigated of which the computational load is much less than that of the Filtered-X LMS method for a long duct or narrow band noise cancellation application This algorithm is based on the hypothesis that the cancellation path model for the Filtered-X LMS method does not have to be accurate and can be represented by a delay in such cases. The steady state weight vector solution in the presence of model error is investigated to show the validity of using an erroneous simplification. The ADE (Adaptive Delay Estimation) method is proposed for effective delay estimation of the cancellation path, which can be used with the Delayed-X LMS algorithm on-line or off-line. Simulation and experimental results demonstrate the effectiveness of the Delayed-X LMS algorithm for the specified applications. (C) 1998 Academic Press Limited.
Keyword:
NOISE
SYSTEM
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
