盲信号分离是当前信号处理研究的热点课题之一，在无线数据通信、医学、语音和地震信号处理等领域有着广阔的应用前景。一种基于负熵最大的FastICA算法用于实现盲信号分离。。该方法的基本思路是以非高斯信号为研究究对象，在独立性假设的前提下，对多路观测信号进行盲源分离。在满足一定的条件下，能够从多路观测信号中，较好地分离出隐含的独立源信号。

-Blind signal separation is one of the hot topics of signal processing research has broad application prospects in the field of wireless data communications, medical, speech and seismic signal processing. Based on negative entropy FastICA algorithm for blind signal separation. . The basic idea of ​ ​ this method is non-Gaussian signal study subjects for the study, the hypothesis of independence, the observed signal of the multi-channel blind source separation. Meet certain conditions, from the signals of multiple observations, good separation of independent source signals implied.