使用可变步长LMS算法的自适应傅立叶分析

Yegui Xiao, Boyan Huang, Hongyun Wei
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引用次数: 5

摘要

自适应傅立叶分析在生物医学工程、音乐信号处理、数字通信、电力工程等领域有着广泛的应用。到目前为止,已经开发和应用了许多自适应算法和系统。本文提出了一种可变步长LMS (VSS-LMS)算法,用于噪声正弦信号的自适应傅里叶分析。它在平稳和非平稳环境中都明显优于传统的LMS和p-power算法,而计算成本的增加很少。通过大量的仿真以及对大型工厂旋转机械产生的真实噪声信号的应用,验证了所提算法改进的性能和跟踪能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Fourier analysis using a variable step-size LMS algorithm
Adaptive Fourier analysis has numerous applications in biomedical engineering, music signal processing, digital communications, power engineering etc. So far, a lot of adaptive algorithms and systems have been developed and applied. In this paper, a variable step-size LMS (VSS-LMS) algorithm is proposed for adaptive Fourier analysis of noisy sinusoidal signals. It significantly outperforms the conventional LMS and p-power algorithms in both stationary and nonstationary environments at the expense of very little increase in computational cost. Extensive simulations as well as application to real noise signals generated by large-scale factory rotating machines are conducted to confirm the improved performance and tracking capabilities of the proposed algorithm.
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