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。
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。
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。
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。
Blind sources separation (BSS) is process of estimating unknown source signals from observed signals which are mixtures of unknown source signals.
信号的盲分离就是从一组由未知源信号混合得到的观测信号中估计源信号的过程。
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。
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。
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。
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。
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。
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