欠定盲信号分离混合矩阵估计新算法

2012 Eighth International Conference on Computational Intelligence and Security Pub Date : 2012-11-17 DOI:10.1109/CIS.2012.90

Cui Zhi-tao, Jian Ke

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引用次数: 1

摘要

根据3个观测信号和4个信号源的欠定盲信号分离，提出了一种估计混合矩阵的新算法。根据SCA模型的几何意义，分析了观测信号的数值特征，证明了欧氏空间下的内积可以对该情况下的观测信号进行分类。此外，给出了一种确定源信号个数的方法，并介绍了一种利用欧氏空间内积结合区间点密度估计混合矩阵的算法。该算法能有效地识别源信号的数量，并能实现混合矩阵的估计。实验结果表明，该算法是可行的。

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A New Algorithm to Estimate Mixing-Matrix of Underdetermined Blind Signal Separation

The paper puts forward a new algorithm to estimate mixing-matrix according to the underdetermined blind signal separation of 3 observed signals and 4 sources. According to the geometric meaning of the SCA model, the paper analyzes the numerical feature of the observed signal and proves that the inner product under Euclidean space can be used to classify the observed signal in the situation. Besides, the paper gives a method for determining the number of source signal and introduces an estimation algorithm for mixing-matrix using inner products in the Euclidean space combined with the density of interval point. The algorithm can effectively identify the number of source signals and can realize the estimation of mixing-matrix. The experimental results show the algorithm is feasible.

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2012 Eighth International Conference on Computational Intelligence and Security

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