摘要
相对于独立成分分析(ICA),相关成分分析(DCA)在实际问题中具有更广泛的应用背景,得到了信号处理研究领域的广泛关注。在ICA方法的基础上,给出了DCA模型的定义、可分离性与分离的唯一性理论,分析了多维ICA模型及其在胎儿心电信号提取中的应用、子带分解ICA模型及其在谐波提取中的应用,具有一定的理论基础和应用背景,在应用问题中,具有一定的参考价值。
Dependent Component Analysis（DCA） as an extended Independent Component Analysis（ICA） model has more applica- tions than ICA and received more and more attentions during the last several years in the study of signal processing, neural network and applications. As two important Blind Source Separation（BSS） methods, DCA and ICA have many relations from the models to the optimal algorithms. In this paper, we briefly review recent advances in BSS for DCA. After a general and detailed definition of the DCA model is given, the relationships between ICA and DCA methods is discuss simultaneously. Moreover, because a funda- mental difficulty in the DCA problem is that it is not unique without extra constraints, the separateness and uniqueness of the DCA model have been discussed and reviewed too. At last, the state-of-art ISA algorithms are overviewed from different theory founda- tions, some DCA algorithms based on the multidimensional ICA and Subband Decomposition ICA Method are constructed for the BSS problem in detail.
出处
《微型电脑应用》
2013年第7期24-26,共3页
Microcomputer Applications
关键词
相关成分分析
盲源分离
独立成分分析
稀疏成分分析
Dependent Component Analysis （DCA）
Blind Source Separation （BSS）
Independent Component Analysis（ICA）
Sparse Component Analysis
