摘要：

提出一种新的独立成分分析算法，在利用直方图估计概率密度函数的基础上，由极大似然函数法构造独立信号的特征，并且在估计概率密度函数时，对相应的阶梯函数采用磨光处理，引入参数 ，并证明了 的选择依赖于信号的统计特征以及采样的样本总数。模拟实验结果表明，该算法能提高信号干扰比。

关键词: 独立成分分析, 直方图估计, 磨光函数, 极大似然估计, Parzen窗

Abstract:

A new Independent Component Analysis(ICA) algorithm is introduced by histogram estimation and maximum likelihood estimation. When estimating the probability density function, the corresponding step function is smoothed using parameter . It is proved that depends on statistical characteristics of signals and total number of samples. Simulation results demonstrate that signal-to-interference ratio has significant improvement.

Key words: Independent Component Analysis(ICA), histogram estimation, smoothing function, maximum likelihood estimation, Parzen window

中图分类号: 

• N945