.png){kind=icon}
返回
Stability analysis of learning algorithms for blind source separation
.png){kind=icon}
PRE
AI
DOI：10.1016/S0893-6080(97)00039-7.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recently a number of adaptive learning algorithms have been proposed for blind source separation. Although the underlying principals and approaches are different, most of them have very similar forms. Two important issues remained to be elucidated further: the statistical efficiency and the stability of learning algorithms. The present letter analyzes a general form of statistically efficient algorithms and gives a necessary and sufficient condition for the separating solution to be a stable equilibrium of a general learning algorithm. Moreover, when the separating solution is unstable, a simple method is given for stabilizing the separating solution by modifying the algorithm. (C) 1997 Elsevier Science Ltd.
Keyword:
blind source separation
stability of learning
efficiency of learning
natural gradient
independent component analysis (ICA)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.3
论文数:
8.2K
被引数:
3.0W
机构
暂无机构信息
引用论文
A unified stability analysis of the Herault-Jutten source separation neural network.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏
查看更多内容