摘要
将半参数统计模型引入源信号个数未知的盲分离中,给出了源信号个数(其值n不大于观测信号的个数m)未知,混合矩阵列满秩时,盲分离半参数统计模型的估计函数,得到了由此估计函数给出的半参数统计学习算法.由于分离模型的任一分离点都是该算法的平衡点,比已有算法有更好收敛稳定性.通过计算机仿真验证了半参数统计学习算法的有效性和良好的收敛稳定性.
The problem of blind source separation (BSS) with an unknown number of sources is considered. Firstly, the semiparametric statistical approach is introduced into the BSS, and an estimating function for the semiparametric statistical approach in BSS is proposed, from which a learning rule is obtained. Each separating point is the equilibrium of the learning rule. Finally, the computer simulation shows that the learning rule obtained from the semiparametric statistical approach has better performance in convergence than the one based on the natural gradient.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2003年第6期844-848,852,共6页
Journal of Xidian University
基金
国家自然科学基金资助项目(60072043
60272058)
关键词
半参数统计
源信号
盲信号分离
自然梯度
互信息
对比函数
估计函数
blind source separation
natural gradient
mutual information
contrast function
semiparametric statistical approach
estimating function