关键词: 独立分量分析, 源识别, 主分量分析, 最大相关准则

Abstract: In order to identify independent sources from a complex system under strong noisy environment, a method for sources recognition based on a compound PCA-ICA network is proposed, by use of such features as principal components pro- jection with PCA and redundancy reduction with ICA. By combining PCA and ICA, their advantages are brought into play well, and every independent sources embedded into multi-channel observation by sensors are separated. By use of an adaptive revision based on fast fourier transform (FFT) and maximum correlation criterion (MCC), blind indeterminacy of the estimated sources by ICA is eliminated effectively, and the sources and their mixing matrix are restored correctly. Thus, different independent sources are recognized. The result of simulation imply that the new method is not only effective, but also of great potential in sources recognition of complex sys- tem.

Key words: Independent component analysis, Maximum correlation criterion, Principal component analysis, Sources recognition