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首页> 外文期刊>IEEE Transactions on Circuits and Systems. I, Regular Papers >Blind-Source Separation Based on Decorrelation and Nonstationarity
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Blind-Source Separation Based on Decorrelation and Nonstationarity

机译：基于解相关和非平稳性的盲源分离

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摘要

In this paper, discrete-time blind-source separation (BSS) of instantaneous mixtures is studied. Decorrelation-based sufficient criteria for BSS of stationary and nonstationary sources are derived based on nonstationarity and nonwhiteness. A gradient algorithm is proposed based on these criteria. A batch-data algorithm and an on-line algorithm are developed based on the corollaries of the BSS criteria. These algorithms are especially useful for the separation of nonstationary sources. They are robust to additive white noises if the time-delayed decorrelation and the nonstationarity of the sources are considered simultaneously in the algorithms. Experiment results show the effectiveness and performance of the proposed algorithms
机译：本文研究了瞬时混合物的离散时间盲源分离（BSS）。基于非相关性和非白度，得出基于去相关的固定和非固定源BSS的充分标准。基于这些标准提出了一种梯度算法。基于BSS标准的推论，开发了批处理数据算法和在线算法。这些算法对于分离非平稳源特别有用。如果在算法中同时考虑了时延去相关和源的非平稳性，则它们对于加性白噪声具有鲁棒性。实验结果表明了所提算法的有效性和性能。

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