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。
Finally, we research the Blind Source Extraction(BSE) of temporally correlated sources.
重点研究了时间相关源的盲提取算法。
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。
Generally, classical BSS methods include Blind source parallel separation and Blind source extract.
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。
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。
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。
The contributions of this paper are followed:1 IntroductionIntroduce the concept "Blind" and present MEMO blind source separation model.
简介介绍“盲”的概念，并对瞬时混合盲源分离系统进行建模。
Noises produced from a working diesel engine are typical blind source signals which could be separated by independent component analysis.
在一段时期内，噪声分离难题一直是制约着柴油机噪声研究、分析、治理工作的一道“瓶颈”。
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。
The model of nonlinear blind source separation(NBSS) is built which the nonlinear transfer function is simulate by the P-th order polynomial function.
用高阶奇数多项式拟合非线性混合函数，建立非线性信号盲分离模型。
Blind source separation is a promising technique for signal processing, which has such features as blind information processing and waveform restoral.
盲源分离是一种很有希望的信号处理技术，具有独特的盲信息处理和波形保持能力。
The separability and separating conditions for mixed signals are analyzed in this paper. The limitation of nonlinear blind source separation methods is proposed.
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 contrast function theory and the optimal algorithm theory are investigated. The Blind source extract theory and algorithm are also investigated emphatically.
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 method is named as speedup gradient method. Based on the method developed, the numerical simulation of vibration signal blind source separation was performed.
利用所建立的方法进行振动信号盲源分离的数值仿真，分离后的信号波形与源信号一致。
Finally, simulation proves the capacity to perform the blind source separation with an unknown number of sources and the convergent stability of the new algorithm.
新算法具有与自然梯度算法相同的收敛速度，而且克服了已有算法不能稳定收敛的缺点。仿真验证了新算法的分离性能和收敛稳定性。
Blind source separation (BSS) aims to extract independent signals from their linear mixtures captured by a number of sensors without knowing the channel information.
线性混叠盲源分离是指观测信号由源信号经线性混合得到，现阶段盲源分离的大多数研究集中于线性混叠模式。
Blind source separation is an efficient method to recover source signals from observed signals, and it has become an attractive research in the field of signal processing.
盲源分离是从观测信号中恢复源信号的一种有效方法，目前已成为信号处理领域的研究热点。
应用推荐