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.
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.
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.
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.
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.
盲信号提取主要研究如何把源信号逐个从观察信号中提取出来。
Blind signal extraction researches mainly on how to extract the source signal sequentially from the mixed signals.
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.
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.
并结合调制信号的恒模特性，提出了基于广义峭度的恒模盲信号提取算法。
Jointed the constant module (CM) character of digital modulated signal, the CM generalized kurtosis algorithm is deduced.
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.
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.
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.
提出一种估计激活函数的新方法，与盲信号抽取定点算法相结合，形成一种新的盲分离算法。
A novel BSS algorithm is presented in this paper by combining the PDF estimation with the fixed-point algorithm.
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.
盲信号处理是信号处理的一种基础技术，它要解决仅仅依靠输出信号去重现整个传输系统的问题。
Blind signal processing is a fundamental signal processing technology aimed at retrieving a system's unknown information from its output only.
计算机仿真结果表明该算法的收敛性能优于粒子群优化算法，并且在非线性盲信号分离中是有效的。
The computer simulation results showed that the proposed algorithm was superior to original particle swarm optimization algorithms and was effective in separating nonlinear blind sources.
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.
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.
在直扩码分多址(DS - CDMA)通信中，盲信号检测及干扰抑制技术是增加系统容量的重要手段。
In direct sequence code division multiple access (DS-CDMA) communications, blind signal detection and interference cancellation are the important methods to increase system capacities.
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.
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.
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.
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.
本文主要研究了数字通信信号MASK,MFSK,MPSK信号的解调技术，重点研究了盲信号处理中通信信号的软件解调。
Demodulation techniques on digital communication signals, such as MASK, MFSK and MPSK signals, is discussed in this paper.
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.
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.
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