Research and development on signal separation techniques which can work effectively for interfaces

该研究项目的目的是提出一种从混合体中恢复移动源和爆炸的分离方法。对于运动源的分离方法，我们提出了三种方法：1.特征向量法、2 A超指数法和3 A波束形成法。特征向量算法可以工作，使得可以通过一次迭代获得恢复源的所需解。超指数方法是可行的，因此恢复源的期望解可以以指数速度获得。在波束形成方面，首先对运动信源进行定位，然后根据定位信息进行波束形成以恢复运动信源。在提出的三种方法中，第三种方法对运动源的分离效果最好。至于分离刘海的方法，我们认为可以使用第三种方法来恢复刘海。关于人机界面有哪些方法合适的问题，我们将继续研究其解决方案。

The objective of the research project is to propose the separation method for recovering moving sources and bangs from their mixtures. As for the method for separating moving sources, we have proposed three kinds of methods : 1. An eigenvector algorithms, 2 A super-exponential method, and 3 A beamforming. The eigenvector algorithm can work such that the desired solution for recovering sources can be obtained with one iteration. The super-exponential method can work so that the desired solution for recovering sources can be obtained with exponential rate. On the beamforming, at first, the localization of moving sources is implemented and then based on the information on the localization, the beamforming is applied to recover the moving sources. Among the three proposed method, the third one is best for separating moving sources. As for the method for separating bangs, we consider that the bang can be recovered by using the third method. On the problem of what are suitable methods for the interface between human and machine, we will continue to investigate its solutions.