Selective-tap blind signal processing for speech separation.
Selective-tap blind signal processing for speech separation.
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用于语音分离的选择性抽头盲信号处理。
DOI：
10.1109/iembs.2009.5334033
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Loizou,PhiliposC
中科院分区：
文献类型：
--
作者：
Kokkinakis,Kostas;Loizou,PhiliposC
本文提出了一种新的盲多通道自适应滤波方案，该方案在更新方程的误差梯度中加入了部分更新机制。所提出的盲处理算法通过仅更新自适应滤波器的选定部分来在时间域中操作。该算法将所有计算资源引导到在误差面上具有最大幅度梯度分量的抽头。因此，它在每次迭代中只需要少量的更新，并且可以极大地减少总体计算复杂性。在实际盲识别场景中进行的数值实验表明，该算法的性能与完全更新算法相当，但具有极大的降低计算复杂度的优点。
In this paper, we propose a new blind multichannel adaptive filtering scheme, which incorporates a partial-updating mechanism in the error gradient of the update equation. The proposed blind processing algorithm operates in the time-domain by updating only a selected portion of the adaptive filters. The algorithm steers all computational resources to filter taps having the largest magnitude gradient components on the error surface. Therefore, it requires only a small number of updates at each iteration and can substantially minimize overall computational complexity. Numerical experiments carried out in realistic blind identification scenarios indicate that the performance of the proposed algorithm is comparable to the performance of its full-update counterpart, but with the added benefit of a highly reduced computational complexity.