Unsupervised FIR adaptive filtering and its frequency domain analysis

Zhen Hua Li*, Jia Bin Chen, Tao Ma

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

An unsupervised minimum mean square error FIR adaptive filtering (UAF) algorithm is proposed to estimate the system's input signal. The algorithm only uses the system's output signal and noise variance without requiring knowledge of a reference signal. The frequency analysis shows that the UAF is a multi-spot bandpass filter with passing frequency determined by the system's input signal. Namely, the UAF chooses the expected frequency and extremely restricts the unwanted frequency signal by using weight-updating scheme in time domain. However, the UAF presents the Gibbs phenomenon since the ideal filter is infinitely long which is unrealizable. The simulation and experimental results show that the UAF could effectively reduce the amplitude of the noise and improve the signal to noise ratio.

源语言英语
页(从-至)234-239
页数6
期刊Journal of Beijing Institute of Technology (English Edition)
21
2
出版状态已出版 - 6月 2012

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Li, Z. H., Chen, J. B., & Ma, T. (2012). Unsupervised FIR adaptive filtering and its frequency domain analysis. Journal of Beijing Institute of Technology (English Edition), 21(2), 234-239.