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.
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。
Abstract: in this paper, several recently proposed neural network approaches to nonlinear blind signal separation (BSS) are reviewed.
摘要：本文回顾了一些最新的求解非线性盲源分离问题的神经网络算法。
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。
Most algorithms for blind signal separation (BSS) have poor performance in a noisy back-ground.
噪声环境下大多数盲源分离+算法性能大大降低。
Blind signal separation (BSS) is an important topic, it also has used in many applications.
盲源分离是一个非常广泛的议题，在许多实际系统中有着应用。
Blind signal separation (BSS) is an important topic, it also has used in many applications.
盲源分离是一个非常广泛的议题，在许多实际系统中有着应用。
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