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Method for Recognition of
Independent Sources of Complex System Under Strong interferences
JIAO
Weidong1, 2 YANG Shixi1 QIAN Suxiang2
YAN Gongbiao1
(1.
Mechanical Engineering Department, Zhejiang University, Hangzhou 312007;
2. College of Mechanical & Electrical
Engineering, Jiaxing University, Jiaxing 314001 )
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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 projection 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: Principal
component analysis Independent component analysis Maximum
correlation criterion Sources recognition
CLC No: TN912.3
国家自然科学基金(50505016)和浙江省自然科学基金(Y105083)资助项目.
Received
20051107, received in revised form 20060404
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