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一种信道盲辨识与均衡的新方法
  • 期刊名称:系统工程与电子技术,正式录用(EI)
  • 时间:0
  • 分类:TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]河南理工大学计算机科学与技术学院,河南焦作454001, [2]西安电子科技大学电子工程学院.陕西西安710071, [3]天水师范学院物理与信息科学学院,甘肃天水741001
  • 相关基金:国家自然科学基金“信源数目未知与动态变化时盲信号分离神经网络方法研究”(60775013)阶段性成果
  • 相关项目:信源数目未知与动态变化时盲信号分离神经网络方法研究
中文摘要:

研究以四阶累积量矩阵为特征矩阵的非正交联合对角化盲分离算法的可辨识性.首先通过分析表明盲分离的目的是寻找与理想分离矩阵本质相等的矩阵.然后证明了理想分离矩阵可以使四阶累积量所构成的特征矩阵对角化.进一步又证明了能使该特征矩阵对角化的矩阵必然与理想分离矩阵本质相等,从而为基于非正交联合对角化盲分离算法提供了理论依据.

英文摘要:

The identifiability of nonorthogonal joint diagonalization blind signal separation(BSS) which was characterized by the fourth-order cumulants matrix was studied in this paper. First, it was demonstrated that the aim of BSS was to pursuit the matrices essentially equaling to ideal separating matrix, and then proved that the eigen-matrices based on fourth-order cumulants could be diagonalized by ideal separating matrices. Furthermore, it proved that the matrices that made eigen-matrices diagonalizing were necessarily equal to the ideal separating matrices. Finally, the theoretical basis was given based on nonorthogonal joint diagonalization for the BSS algorithms.

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