自适应波束形成可以实现空间信号分离。
Spatial signal separation can be realized by adaptive beamforming technique.
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.
采用目标信号分离与滤波可进一步提高制导精度。
To use separation of goal signal and wave filter, the guided precision can be improved.
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.
提出了基于相关性的瞬时线性混合盲信号分离算法。
An algorithm based on the correlation characters for instantaneous linear mixture of the source signal is proposed.
但在实际应用于机械源信号分离中，效果尚不够理想。
However, the effect of sources separation by such method is not adequate for mechanical sources in practice.
本文用双层的细胞神经网络(CNN)进行盲信号分离。
In this paper a two-layer cellular neural network (CNN) is used to separate blind signals.
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。
The second, it uses this method to blind speech signals separation of more sources than sensors.
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.
在盲信号分离中，用串音误差：作为衡量信号分离的性能指标。
In the blind signal separation, with the crosstalk error: signal separation as a measure of the performance indicators.
一般来说，盲信号分离包括盲信号并行分离和盲信号提取两种方法。
Generally, classical BSS methods include Blind source parallel separation and Blind source extract.
还需要在测扭振传感器获得的振动信号中把横振引起的信号分离出去。
It is also necessary to separate signals brought by transverse vibration from vibration signals, obtained by sensors used for measuring torsional vibration.
由于关于混合信号的信息完全未知，因此将该过程称为盲源信号分离。
Except that the source signals are assumed to be independent, no apriori information is known about the mixture signals. That is why the problem is known as Blind Source Separation.
经营的距离，是从积极的传感器表面上的一个开关信号分离产生的对象。
The operating distance is the separation of an object from the active sensor surface at which a switching signal is produced.
提出了一种基于WHT的多分量LF M信号的参数估计与信号分离算法。
A new algorithm of the parameter estimation and the signal separating is presented based on multi-component LFM signal with the WHT.
自适应滤波广泛应用于系统识别、信号分离、信道均衡以及回声抵消等领域。
Adaptive filtering is widely used in system identification, signal separation, channel equalization and echo cancellation and other fields.
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.
从回波信号中进行多目标信号分离和提取始终是防撞雷达的一个关键技术难点。
It is more difficult to estimate and separate LFM as a result of the appearance of multi-object and the applying of Multi-LFM radar wave signal.
近几十年来，盲信号分离因为它在多种问题上的应用潜力受到广大研究者的重视。
Over the past decades, Blind source separation (BSS) has received much research attention because of its potential applicability to many problems.
本文基于一个全连接递归网络结构，给出一种新的信息理论的盲源信号分离准则。
A new information theory criterion for blind source separation based on a recurrent neural network is proposed.
在偏时域相干算法的基础上，采用自适应滤波分析技术，是一种新的信号分离算法。
It is a new kind of signal separation algorithm base on the partial time-domain coherent algorithm USES the adaptive filter analysis technology.
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.
对测试中所得的力信号和应交信号进行了信号分离，同时，对应交误差进行了修正。
Signal separation were completed for the measured force and strain signals, and the strain errors were calibrated.
现有的混合混沌信号分离方法一般都要利用各个混沌信号的内在性质以及一定的约束。
The results by computer simulation indicate that the mixed chaotic signals, by using the method, the source signals can be separated fast and effectively.
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.
研究了盲信号分离的对比函数理论和优化算法理论，着重研究了盲信号提取理论及其算法。
The contrast function theory and the optimal algorithm theory are investigated. The Blind source extract theory and algorithm are also investigated emphatically.
K最近邻的信号分离算法中，较多地采用了乐音信号的先验信息，一定程度上可实现信号分离。
The KNN based music source separation algorithm utilizes prior information of music source which can also achieve music source separation.
该方法相对信号分离的松驰算法、高阶累积量算法及循环平稳类算法而言，具有运算量小的优势。
The JJM has slight computation burden compared with the RELAX method, high-order cumulate method, and cyclostationarity algorithms.
小波变换技术具有很强的信号分离能力容易把随机噪声从信号中分离出来，从而提高信号的信噪比。
Wavelet Transfer (WT) is a powerful technique in signal separation. It is very easy for WT to improve the signal-to-noise (SNR) by separating the random noise and useful signal.
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