摘要：

基于主成分分析技术、独立分量分析技术以及多数据流模型，将用于数据和信号分析的PCA/ICA方法应用于多数据流模型，提出多数据流关联度分析和模式发现的新模型。该模型适用于解决在线混合数据流分离，对挖掘多数据流潜在独立内因有良好效果。探讨模型的健壮性和实时性，并在实验中验证了系统性能。

关键词: 数据流, 主成分分析, 独立成分分析, 多数据流关联

Abstract:

This paper introduces a model based on Principal Component Analysis(PCA), Independent Component Analysis(ICA) and multiple data stream model which supplies a new method of multiple data stream relation analysis and pattern discovery. As PCA/ICA can separate independent components from complicated information, a solution can be implemented with the help of PCA/ICA on multiple data stream relation analysis, pattern discovery and hidden variables. The robustness and real-time performance are also discussed in the experiment.

Key words: data stream, Principal Component Analysis(PCA), Independent Component Analysis(ICA), multiple data stream relation

中图分类号: 

• TP311