LMS、NLMS、RLS和QR-RLS算法在车辆噪声抑制中的比较

Proceedings of the 10th International Conference on Computer Modeling and Simulation Pub Date : 2018-01-08 DOI:10.1145/3177457.3177502

R. Martínek, R. Kahankova, J. Nedoma, M. Fajkus, M. Skacel

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引用次数: 10

摘要

本文主要研究语音处理和自适应滤波。为了进行分析，我们使用了在LabVIEW中在线和离线模式下实现的应用程序。实验包括用NI 9234对电动汽车和柴油车的噪声进行测量和分析，以及应用实例。我们测试了四种不同的自适应滤波器来消除噪声，并比较了它们的效率。比较各个算法效率的标准主要是提高全局信噪比(GSNR)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparison of the LMS, NLMS, RLS, and QR-RLS algorithms for vehicle noise suppression

The paper deals with the speech processing and adaptive filtration. For the analysis we used application implemented in both online and offline mode in LabVIEW. The experiments included comparison of the noise caused by electric car and diesel car which was measured and analyzed by means of Microphones NI 9234 and our application. We tested four different adaptive filters to cancel the noise and compared their efficiency. The criterion for comparing the efficiency of individual algorithms is primarily to increase the global signal to noise ratio (GSNR).

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Proceedings of the 10th International Conference on Computer Modeling and Simulation

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