Blind sources separation (BSS) is process of estimating unknown source signals from observed signals which are mixtures of unknown source signals.
信号的盲分离就是从一组由未知源信号混合得到的观测信号中估计源信号的过程。
Blind sources separation is a special tool for analyzing and processing signals blindly, which is promising in condition monitoring and fault diagnosis of machinery.
盲源分离是一个很独特的盲信号分析与处理工具，在机械设备状态监测与故障诊断领域有较好的应用前景。
New method to blind sources separation based on band-pass filter has been proposed in this paper on the basis of analyzing the present methods of blind sources separation.
本文在分析现有盲源分离算法的基础上，提出一种新的、基于带通滤波的改进盲源分离方法。
Blind sources separation is becoming the problem that gets more and more focus because of broad application in many fields, such as communication, speech recognition and so on.
因为盲信号分离在通信，语音识别等相关领域的广泛应用，使得它成为近年来信号处理研究的热点问题之一。
Blind sources separation is a special and dominant tool for analyzing and processing signals blindly, which is promising in condition monitoring and fault diagnosis of machinery.
盲源分离是一个很有优势的盲信号分析与处理工具，在机械状态监测与故障诊断领域有较好的应用前景。
Blind Sources Separation (BSS) provides a new alterative for extraction of certain signal components in the signal corrupted by noise, and presents a new method for mechanical fault diagnosis.
盲源分离应用于机械振动信号的预处理中，提供了一个新的处理机制，在机械状态监测和故障诊断中具有一定的价值。
Blind separation of sources consists of recovering a set of signals in which only instantaneous linear mixing are observed.
盲源分离的目的在于只利用观测数据把被瞬时线性混合的源信号恢复出来。
Blind separation of sources based on higher order cumulants is applied to the separation between vibration signal and noise, which is important to diagnosi.
本文利用基于高阶累积量的盲信号分离方法，设计了相应算法，成功地从被噪声污染的信号中恢复源振动信号，从而可确保碰摩故障的检测和诊断能顺利进。
A new unified method for the blind separation of sparse sources with unknown source number is proposed.
提出了一种新的用于未知数量稀疏源盲分离的统一方法。
It is proposed a new blind separation algorithm of ill-condition mixed sources.
提出了一种新的病态混叠盲源分离算法。
It is proposed a new blind separation algorithm of ill-condition mixed sources. Observed signals are pre-processed through eliminating redundancy signals so that mixed matrix A is row full rank.
提出了一种新的病态混叠盲源分离算法。算法首先对观察信号进行预处理，把多余的观察信号剔除，使预处理后的混叠矩阵A是行满秩的；
Finally, simulation proves the capacity to perform the blind source separation with an unknown number of sources and the convergent stability of the new algorithm.
新算法具有与自然梯度算法相同的收敛速度，而且克服了已有算法不能稳定收敛的缺点。仿真验证了新算法的分离性能和收敛稳定性。
The second, it uses this method to blind speech signals separation of more sources than sensors.
然后将此方法用于多信源少观测源情况下的混合语音信号分离。
This paper presents an algorithm and a corresponding networks to deal with blind separation of sources in the case of singular mixing matrix.
混合信号盲分离问题是一类很难而又具有很强应用背景的问题，以往对这类问题的研究均在混合矩阵为非奇异的条件下进行。
The problem of overdetermined Blind source Separation (BSS) where there are more mixtures than sources is considered.
该文研究超定盲信号分离，即观测信号个数不少于源信号个数情况下的盲信号分离问题。
The problem of overdetermined Blind source Separation (BSS) where there are more mixtures than sources is considered.
该文研究超定盲信号分离，即观测信号个数不少于源信号个数情况下的盲信号分离问题。
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