.png){kind=icon}
返回
Two-gradient direction FXLMS: An adaptive active noise control algorithm with output constraint
.png){kind=icon}
OA
AI
DOI：10.1016/j.ymssp.2018.06.062.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Active noise control (ANC) is broadly used to cancel the unwanted disturbance in different fields because of its excellent performance in abating low-frequency noise. In practice, however, the limited driving capability of actuators restrict the maximum output power of ANC systems. Once the driving signal of the ANC system exceeds these limitations, the inherent nonlinearity of the actuators will deteriorate the noise reduction and may result in the divergence of the adaptive algorithm. Hence, the two-gradient direction filtered-x least mean square (2GD-FXLMS) algorithm based on the optimal Kuhn-Tucker solution with the output constraint is proposed in this paper. This algorithm has the advantage of minimizing system overdriving, maintaining a specified power budget, and enhancing system stability. Compared to existing output-constrained adaptive algorithms, this proposed algorithm has the same computational complexity as the conventional FXLMS algorithm, while maintaining a stricter output constraint that minimizes the saturation distortion. (C) 2018 Elsevier Ltd. All rights reserved.
Keyword:
Saturation distortion
Constrained optimization
Kuhn-Tucker solution
Nonlinear active noise control
Filtered-x least mean square algorithm
Hemstitching method
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。
期刊
IF:
8.9
论文数:
1.3W
被引数:
6.6W
机构
引用论文
Advances in active noise control: A survey, with emphasis on recent nonlinear techniques.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏
查看更多内容