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《Journal of Guangdong Ocean University》 2009-04
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Sparse Component Analysis for Underdetermined Blind Source Separation

LI Chang-li(School of Information Engineering,Guangdong Ocean University,Zhanjiang 524088,China)  
The main method,namely,sparse component analysis(SCA),which is used to solve underdetermined BSS,is analyzed.This class of methods consists of two stages: first clustering and then optimization,all of which firstly estimate the mixing matrix and then estimate the source signals given the estimated mixing matrix by means of optimization.Various algorithms for clustering and optimization in underdetermined BSS are summarized,and the close relationship between underdetermined BSS,SCA and compressed sensing is discussed.Finally prospect for underdetermined BSS is made.
【Fund】: 广东省自然科学基金项目资助(7010116)
【CateGory Index】: TN911
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【Citations】
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【Co-citations】
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6 CHEN Chao1,GAO Xian-jun1,LI De-xin2(1.Department of Aviation Electronical Engineering,The Aviation University of Air Force,Changchun 130022,China;2.The Flight Simulation Research Institute of Air Force,Harbin 150001,China);Overlapped Frequency-Hopping Communication Signals Separation Algorithm Based on Independent Component Analysis[J];Journal of Jilin University(Information Science Edition);2008-04
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9 ZHENG Hang-xing①②,YANG Li①,SHEN Zhi-ming②(①Institute of Surveying and Mapping,Information Engineering University, Zhengzhou 450052,China;②61365 Troops, Tianjin 300140,China );Utilizing Rosenbrock method to optimize coordinate transformation[J];Science of Surveying and Mapping;2008-02
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