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.
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.
通过对传统盲源分离批处理EASI算法的分析，针对时变信道中通信信号的复数形式，以平滑窗的形式实现了批处理算法在时变混合模型下的应用。
Based on an analysis of EASI batch process algorithms for traditional blind source separation, a sliding window ICA algorithm is studied to deal with complex signals in the time variant mixing model.
本文研究了后非线性混合信号的盲分离。
The problem of blind separation of signals in post nonlinear mixture is addressed 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.
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 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.
介绍了ICA的原理、含义及EASI算法，并仿真了该算法在语音信号盲分离中的应用。
This paper presents the principle, definition and EASI algorithm of ica, and describes the application of the algorithm in the field of speech signal processing.
本文从信息论的角度入手，研究线性卷积混合的盲解卷积问题，成功实现了基于信息最大化准则的反馈网络算法对两源信号的分离。
From the perspective of information, the paper studies the linear blind deconvolution, successful separate two sources based on information maximization algorithm to the feedback network.
研究了实际环境语音信号的特性，结合语音信号的短时平稳性和长时非平稳性，给出了一种时频域盲分离算法。
Investigation characteristic of real world audio, combine stationary for short time-scale and non-stationary for longer time-scales, proposed a time frequency domain blind source separation algorithm.
论文介绍了基于核空间的ICA的原理和基本算法，然后介绍了该算法与典型ICA和主成分分析(PCA)在盲源信号分离中的比较。
In this paper, kernel independent component analysis (KICA) 's principle and algorithm are introduced, and then the KICA comparison with some other ICA and principal component analysis (PCA) is given.
文中分析了水声基阵接收信号的实数延时模型和复数混合模型，提出了水声信号盲分离算法性能评价准则。
According the real domain algorithms, we present the evaluating criterion to the complex algorithms for blind underwater acoustic signals separation.
并且以线性瞬时混合信号为例，实现了对一般信号、声音信号和图像信号以峰度为判别依据的盲分离和抽取。
And we take the linear instantaneous mixtures as an example, and put it into realty in general signals, sound signals and image signals based on kurtosis.
将其用于盲源分离，通过实例证明了该方法的正确性和有效性，从而解决了盲分离中信号源个数的估计问题，为盲源分离技术的应用进一步奠定了基础。
The validity of the method in BSS is proved through experiments. Thus the method can solve the problem of estimation of signal number in BSS, it paves the way to wider application of BSS methods.
研究后非线性混合信号的盲分离，从最大似然角度推导了一般后非线性分离结构的学习公式；
The problem of blind separation of signals in post-nonlinear mixture is addressed. The learning rules for the general post-nonlinear separation structure are derived by a maximum likelihood approach.
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.
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.
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