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A two-stage-type algorithm is presented for blind source separation in the overdetermined instantaneous mixture case. The algorithm accomplishes two tasks: blind identification for estimating the mixing matrix and source estimation for recovering the original source signals with the identified mixing matrix. In this paper, we focus on the former task. A new mixing matrix identification method, which...
In this paper, we develop a new deflation-based blind source extraction (BSE) algorithm to estimate and extract source signals in a sequential fashion from the mixtures. At the beginning of this algorithm, the first source signal is estimated by a constrained optimization and its efficient updating rule. Then, the other source signals are estimated and extracted by an exact solution subspace searching-based...
An orthogonal subspace-based method is proposed for the blind separation of convolutive mixtures of nonstationary colored signals. The proposed method relies on eigenvalue decomposition (EVD) of a specially constructed matrix, which contains inform from two orthogonal subspaces. A multiple-input multiple-output (MIMO) blind deconvolution problem can be converted to multiple single-input multiple-output...
A novel algorithm for blind separation of instantaneous linear mixtures of source signals is proposed. The proposed algorithm is based on the generalized singular value decomposition of a matrix pencil. We use a set of linear combinations of time-delayed correlation matrices to estimate the mixing matrix. Simulation results show that the proposed algorithm has better performance in accuracy comparing...
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