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低成本、高保真、自适应消除周期性 60Hz 噪声。

Low-cost, high-fidelity, adaptive cancellation of periodic 60 Hz noise.

机构信息

Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX 78712, USA.

出版信息

J Neurosci Methods. 2009 Dec 15;185(1):50-5. doi: 10.1016/j.jneumeth.2009.09.008. Epub 2009 Sep 16.

Abstract

A common method to eliminate unwanted power line interference in neurobiology laboratories where sensitive electronic signals are measured is with a notch filter. However a fixed-frequency notch filter cannot remove all power line noise contamination since inherent frequency and phase variations exist in the contaminating signal. One way to overcome the limitations of a fixed-frequency notch filter is with adaptive noise cancellation. Adaptive noise cancellation is an active approach that uses feedback to create a signal that when summed with the contaminated signal destructively interferes with the noise component leaving only the desired signal. We have implemented an optimized least mean square adaptive noise cancellation algorithm on a low-cost 16 MHz, 8-bit microcontroller to adaptively cancel periodic 60 Hz noise. In our implementation, we achieve between 20 and 25 dB of cancellation of the fundamental 60 Hz noise component.

摘要

在神经生物学实验室中,消除敏感电子信号测量中的不需要的电源线干扰的一种常见方法是使用陷波滤波器。然而,由于存在固有频率和相位变化,固定频率陷波滤波器无法去除所有的电源线噪声污染。克服固定频率陷波滤波器局限性的一种方法是使用自适应噪声消除。自适应噪声消除是一种主动方法,它使用反馈来创建一个信号,当与受污染的信号相加时,会产生破坏性干扰噪声分量,只留下所需的信号。我们已经在低成本的 16MHz、8 位微控制器上实现了优化的最小均方自适应噪声消除算法,以自适应地消除周期性的 60Hz 噪声。在我们的实现中,我们实现了对基本 60Hz 噪声分量的 20 到 25dB 的消除。

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