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。
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.
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。
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。
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 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。
A novel approach of deterministic blind beamforming (DBBF) for broadband nonstationary source separation is presented in this paper.
提出了一种用于分离宽带非平稳信源的盲波束算法。
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。
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。
A new blind source separation (BSS) algorithm is proposed.
提出了一种新的信号源盲分离算法。
A new unified method for the blind separation of sparse sources with unknown source number is proposed.
提出了一种新的用于未知数量稀疏源盲分离的统一方法。
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。
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。
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。
A new adaptive blind source separation algorithm of non-stationary signals was presented by using natural gradient rule and time-correlation property of the source signals acting on a cost function.
基于自然梯度原则并利用信号的时间相关属性对一类代价函数进行推导，获得一种新的非平稳信号自适应盲分离算法。
In this paper, a convolutive blind source separation (BSS) algorithm based on a double-iteration method is proposed to process the convolutive mixed non-white broadband signals.
本文提出一种基于双迭代方法的关于卷积混迭宽带非平稳有色信号的盲源分离算法。
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。
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.
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。
For separating source signals efficiently, a nonlinear blind separation algorithm based on specific-designed multiobjective evolutionary algorithm is proposed.
设计了多目标进化算法来求解代价函数的全局最优解，提出了非线性盲源分离的多目标进化算法。
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。
Proposed a new mixed-signal blind sound source separation method: This method is based on joint probability distribution of signal statistics!
从盲声源信号的独立性出发！提出了一种新的盲声源混合信号分离方法：该方法基于信号联合概率的分布统计！
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。
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。
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