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In this paper, we propose a novel algorithm for underdetermined blind identification problem in blind source separation. The proposed algorithm is based on the charrelation matrix of observed signals. The charrelation matrix not only can be considered as a generalized second-order covariance matrix, but also incorporates higher-order information. It is significant for blind separation problem based...
A novel underdetermined blind identification algorithm based on charrelation matrix and tucker decomposition is developed. The charrelation matrix is a generalization of covariance matrix, encompassing statistical information beyond second-order while maintaining a convenient 2-dimensional structure. The core functions of charrelation matrices in different processing-points are stacked as a three-order...
In this paper, we develop a blind user separation method using charrelation matrix to improve the blind separation performance of DS-CDMA systems. The charrelation matrix, which is off-origin of the Hessian matrix of the second characteristic function, can be considered as a generalization of the covariance matrix. The problem of blind user separation can be converted as the joint diagonalization...
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