基于改进最小均方的电磁干扰消除研究

Naizhao Yu, Jiahao Wang, Lanyong Zhang
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引用次数: 1

摘要

提出了一种用于非平稳随机信号滤波的自适应干扰抵消算法。设计了一种基于经验模态分解(EMD)分析的智能电磁干扰测量系统。利用经验模态分解(EMD)将复杂的电磁辐射信号分解成不同的自然模态函数,代表不同频率的信号。将改进的最小均方算法应用于自适应干扰消除。结果表明,该方法比传统的自适应消噪方法具有更好的消噪能力。同时,新的自适应干扰抵消技术提高了电磁辐射测量的速度和精度。因此,可以将其引入工程应用。与其他传统仪器和人工测试相比,该系统提高了测试效率,具有良好的可扩展性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Electromagnetic Interference Canceller Based on Improved Least Mean Square
In this paper, a novel adaptive interference cancellation algorithm for non-stationary random signal filtering is proposed. An intelligent Electromagnetic Interference measurement system based on Empirical Mode Decomposition (EMD) analysis is designed. the complex electromagnetic radiation signal is decomposed into different natural mode functions by empirical mode decomposition (EMD), which represent signals with different frequency. An improved least mean square (LMS) algorithm is applied to adaptive interference cancellation. The results show that this method has better noise cancellation ability than the traditional adaptive noise cancellation method. At the same time, the new adaptive interference cancellation technology improves the speed and accuracy of electromagnetic radiation measurement. Therefore, it can be introduced into engineering application. Compared with other traditional instruments and manual testing, the system improves the testing efficiency and has good scalability
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