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  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、语音以及地震信号处理等领域有着广阔的应用前景。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 the study of signal processing, one of the hot topics in wireless data communications, medical, speech and seismic signal processing and other fields have broad application prospects. Negentropy based on the largest FastICA Algorithm for Blind Signal Separation realize. The basic idea is based on non-Gaussian signal as the research object, in the independence assumptions on the multi-channel observation signal blind source separation. In meeting certain conditions, be able to multi-channel observation signal, the better to isolate the independent source signal implied.)

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