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.
盲信号分离系统可以采集真实语音信号，然后使用不同的盲信号分离算法分离。
Blind signal separation system can capture the true voice signals and use a different algorithm to separate.
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.
在简化了一般的盲信号分离模型基础上，阐述了该算法的分离准则并对其自适应收敛算法进行了推导。
We analyze the model of separation system, separation criteria and give the deviation of adaptive algorithm of blind signal separation.
实验结果表明，优化后的盲信号分离算法能够在一定程度上降低算法的运算量，并能得到很好的分离效果。
The experiment shows, the algorithm can considerably reduce the calculation burden and the output speech signals are well separated.
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。
Blind separation of sources based on higher order cumulants is applied to the separation between vibration signal and noise, which is important to diagnosi.
该文分析了非线性混叠信号的可分离性及分离条件，指出现阶段非线性混叠信号盲分离的局限性。
The separability and separating conditions for mixed signals are analyzed in this paper. The limitation of nonlinear blind source separation methods is proposed.
一种新的实时线性混叠信号盲分离算法在本文提出。
A new kind of blind separation algorithm for real time linear mixture signals is presented in this paper.
基于空间时频分布的盲源分离算法可以用来分离具有不同时频分布的信号。
Blind source separation (BSS) based on spatial time frequency distribution can separate signals with different time frequency distributions.
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.
本文提出一种基于双迭代方法的关于卷积混迭宽带非平稳有色信号的盲源分离算法。
In this paper, a convolutive blind source separation (BSS) algorithm based on a double-iteration method is proposed to process the convolutive mixed non-white broadband signals.
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.
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 is a special and dominant tool for analyzing and processing signals blindly, which is promising in condition monitoring and fault diagnosis of machinery.
本文针对盲信号分离中，如何根据信号特征进行有序提取的问题进行了探讨，提出了一种基于遗传算法的有序盲信号提取算法。
We have discussed about how to extract signal in older according to signals 'character in this paper, which is an important problem in the subject of blind separation.
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.
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.
采用基于二阶统计量的盲源分离算法对多导表面肌电信号进行处理，实现噪声的分离和表面肌电信号的初步分解。
Some methods of SEMG signal pretreatment based on blind source separation using second order statistics were proposed for noise separation and the elementary decomposition of multi-channel SEMG.
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。
Blind sources separation is a special tool for analyzing and processing signals blindly, which is promising in condition monitoring and fault diagnosis of machinery.
基于动态逼近的思想，提出了一种新型的信号盲分离迭代算法。
Based on dynamic approximation, this paper presents a new type of iterative algorithm to blind source separation.
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 consists of recovering a set of signals in which only instantaneous linear mixing are observed.
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 becoming the problem that gets more and more focus because of broad application in many fields, such as communication, speech recognition and so on.
基于自然梯度原则并利用信号的时间相关属性对一类代价函数进行推导，获得一种新的非平稳信号自适应盲分离算法。
A new adaptive blind source separation algorithm of non-stationary signals was presented by using natural gradient rule and time-correlation property of the source signals acting on a cost function.
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.
基于提高被动声纳的检测能力，对水声信号的盲源分离技术进行了探索性研究。
To improve the detection performance of passive sonar, present dissertation addresses the blind separation of underwater acoustic signals.
本文提出了用盲信号分离提取胎儿心电的方法。
A new method of blind signal separation was provided to achieve FECG (Fetal ECG) detection.
在许多盲信号源分离算法中，大多需要选择合适的非线性函数或者需要计算信号的高阶统计量。
In many algorithms for blind source separation, most of them must select nonlinear function or compute high-order statistical values.
利用各源信号之间的统计独立性和通信信号的循环平稳性，提出了一种适合于分布式天线接收的混合通信信号盲分离的思想和实现方法。
Based on the statistic independence of sources and the cyclo stationarity of communication signals, an idea and approach to separate the mixed signals received by distributed antennas is proposed.
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 (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 (BSS) is process of estimating unknown source signals from observed signals which are mixtures of unknown source signals.
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