It is proposed a new blind separation algorithm of ill-condition mixed sources.Observed signals are pre-processed through eliminating redundancy signals so that mixed matrix A is row full rank.Further
we propose a cost function that is a logarithm of a ratio of the covariance of a part sum of recovered signals and the covariance of recovered signals so that optimizing this function transform to solve a generalized eigenvalue problem.Under a loose condition
it is proved that any source signals theoretically satisfying the condition can be separated.The computer simulation shows its outstanding performance on blind source separation approach.
Algorithm to Eliminate Permutation of Frequency Domain Blind Source Separation Based on Influence Factor
Blind Recovery of Mixing Matrix with Sparse Sources Based on Improved K-means Clustering and Hough Transform
Variable Step-Size Blind Source Separation Algorithm with an Auxiliary Separation System
Blind Separation of Nonstationary Sources in Impulse Noise
Related Author
LI Zhong-qun
FAN Xiao-teng
FANG Ge-feng
YIN Bai-Qiang
HE Yi-gang
BO Xiang-lei
PENG Xi-yuan
QIAO Li-yan
Related Institution
National Key Laboratory of Science & Technology on Electronic Test & Measurement The 41st Research Institute of China Electronics Technology Group Corporation Qingdao Shandong China
School of Electrical Engineering and Automation Hefei University of Technology Hefei Anhui China
College of Electrical and Information Engineering Hunan University Changsha Hunan China
National Key Laboratory of Science & Technology on Electronic Test & Measurement, The 41st Research Institute of China Electronics Technology Group Corporation
School of Electrical Engineering and Automation, Hefei University of Technology