Another is the single blind source separation algorithm.
另一支是单通道盲源分离算法的研究。
A new blind source separation (BSS) algorithm is proposed.
提出了一种新的信号源盲分离算法。
Blind source separation is put forward to solve the problem well.
盲源分离问题的提出很好地解决了这一难题。
We present a new neural network algorithm for blind source separation.
本文提出了一种新的盲信号分离的神经网络算法。
The subject of this article is about the Blind Source Separation (BSS).
论文的主要研究对象是盲源分离问题。
Speech enhancement based on blind source separation with post-processing in subband.
基于子带盲源分离和后置处理的语音增强方法。
Blind source separation technique is an important branch in blind signal processing field.
盲源分离技术是盲信号处理领域的一个重要的分支。
The blind separation of convolution mixture signals is a nodus in blind source separation.
卷积混叠的盲信号分离是盲源分离问题中的难点。
In the blind source separation algorithm, people usually know something about the sources.
在盲源分离算法中，人们对源信号多多少少会有一点了解。
The blind source separation can extract the feature signals of each machine from the mixed signals.
盲源分离技术可以有效去除环境噪声的干扰并提取出各设备的特征信号。
A new blind source separation algorithm based on information maximization is proposed in this paper.
提出了一种基于信息最大准则的盲源分离新算法。
The blind source separation method has great potential application for the radar signal's seperation.
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 fault diagnosis method based on Local wave time-frequency images is developed.
提出了一种基于局域波时频图像的盲源分离故障诊断方法。
This paper describes the basic theory of blind source separation and natural gradient algorithm in detail.
本文在介绍了盲源分离的基础理论的基础上，对自然梯度算法进行了详细的介绍。
The most two popular algorithms are Computational Auditory Scene Analysis (CASA) and Blind Source 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。
A new information theory criterion for blind source separation based on a recurrent neural network is proposed.
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。
Based on dynamic approximation, this paper presents a new type of iterative algorithm to blind source separation.
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。
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。
A method of forecasting the total solar irradiance based on blind source separation (BSS) neural network was presented.
提出一种应用盲分离神经网络预测逐日太阳辐射能的方法。
A method using demodulated resonance technique based on blind source separation is developed for gear contact diagnosis.
提出一种运用基于盲源分离的共振解调技术对齿轮齿面接触故障进行诊断的方法。
Introduce the concept of waveform similarity to deal with the two two inherent uncertainties of Blind Source Separation.
对于盲源分离的两个固有不确定性问题，引入波形相似度的概念，使问题得到解决。
A method of forecasting the total solar irradiance based on blind source separation (BSS) neural network was pre - sented.
提出一种应用盲分离神经网络预测逐日太阳辐射能的方法。
The basic thought is to apply the existing blind source separation (BSS) algorithm to the signal detection in MIMO-OFDM systems.
基本思想是将现有的盲信源分离算法(BSS)应用到MIMO - OFDM系统的信号检测中。
In many algorithms for blind source separation, most of them must select nonlinear function or compute high-order statistical values.
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。
Finally, the linear blind source separation algorithm based on signal sparse property is applied to the parameterized mixing signals.
最后，在参数空间中，应用基于信号稀疏特性的线性盲分离方法对信号进行分离。
Blind source separation (BSS) based on spatial time frequency distribution can separate signals with different time frequency distributions.
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。
This paper discusses the recoverability of underdetermined blind source separation(BSS), based on a two-stage sparse representation approach.
基于一种两步稀疏表示的方法，利用随机框架讨论欠定盲源分离的恢复能力。
A time-domain Multi-Stage Algorithm(MSA) based on the second order statistics for blind source separation of convolutive mixtures is proposed.
该文提出一种基于二阶统计量的时域多步分解算法求解卷积混合盲源分离问题。
Over the past decades, Blind source separation (BSS) has received much research attention because of its potential applicability to many problems.
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.
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。
应用推荐