Abstract
Adaptive filtering algorithm is one of the most active research topics in signal processing at present. Speech signal processing is the hot issue in the field of digital signal processing. Based on theoretical research of adaptive filter, the work simulated Least mean square error (LMS) adaptive filtering algorithm under different signal-to-noise ratios, spreading to speech signal sequences of different sampling rates. By changing sampling rate factors and filter orders, the work discussed adaptive filtering problems of LMS algorithm under narrowband and broadband interference. Simulation result is consistent with theoretical analysis. With good noise reduction effect, this algorithm is simple and easy to implement.
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Acknowledgements
This work was supported in part by Jiangsu Policy Guidance (Industry University Research) Project (Grant no. BY2016030-16), Major horizontal project (Grant no. KYH15052), Talent Introduction Project (Grant no. KYY15016) and Jiangsu Planned Projects for Postdoctoral Research Funds (Grant no.1601138B).
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Liu, R., Xu, H., Zheng, E. et al. Adaptive filtering for intelligent sensing speech based on multi-rate LMS algorithm. Cluster Comput 20, 1493–1503 (2017). https://doi.org/10.1007/s10586-017-0871-y
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DOI: https://doi.org/10.1007/s10586-017-0871-y