卷积混叠的盲信号分离是盲源分离问题中的难点。
The blind separation of convolution mixture signals is a nodus in blind source separation.
本文提出了一种新的盲信号分离的神经网络算法。
We present a new neural network algorithm for blind source separation.
考虑典型的盲信源分离问题，用自然梯度算法实现盲信号分离。
Consider the typical problem of blind source separation, natural gradient algorithm using blind signal separation.
目前常用的语音分离方法主要有听觉场景分析法和盲信号分离法。
The most two popular algorithms are Computational Auditory Scene Analysis (CASA) and Blind Source Separation.
盲源分离方法是近年来出现的一种先进的信号处理方法。
Method for Blind Separation of sources is the Modem Processing Method for Signal.
同时指出将盲分离方法用于雷达信号的分离，具有广阔的应用前景。
The blind source separation method has great potential application for the radar signal's seperation.
实验结果证明了该算法能够有效用于高维情况下多信源少观测源的盲语音信号分离。
Results of the experiment show that the method is effective for blind speech signals separation.
研究含噪模型的信号盲分离问题具有广泛的应用前景。
The noise model study with blind signal separation issue has broad application prospects.
盲源分离技术是盲信号处理领域的一个重要的分支。
Blind source separation technique is an important branch in blind signal processing field.
针对目前欠定盲分离问题中源数未知，采取“两步法”进行分离源信号。
The two-step approach is often used to separate sources in underdetermined blind separation problem.
提出了一种新的信号源盲分离算法。
在盲源分离算法中，人们对源信号多多少少会有一点了解。
In the blind source separation algorithm, people usually know something about the sources.
在盲源分离算法中，人们对源信号多多少少会有一点了解。
In the blind source separation algorithm, people usually know something about the sources.
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