Source number estimation and separation algorithms of underdetermined blind separation

来源 :Science in China(Series F:Information Sciences) | 被引量 : 0次 | 上传用户:haohaodezuzut
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Recently,sparse component analysis (SCA) has become a hot spot in BSS re-search. Instead of independent component analysis (ICA),SCA can be used to solve underdetermined mixture efficiently. Two-step approach (TSA) is one of the typical methods to solve SCA based BSS problems. It estimates the mixing matrix before the separation of the sources. K-means clustering is often used to estimate the mixing matrix. It relies on the prior knowledge of the source number strongly. However,the estimation of the source number is an obstacle. In this paper,a fuzzy clustering method is proposed to estimate the source number and mixing matrix simultaneously. After that,the sources are recovered by the shortest path method (SPM). Simulations show the availability and robustness of the proposed method. Recently, sparse component analysis (SCA) has become a hot spot in BSS re-search. Instead of independent component analysis (ICA), SCA can be used to solve underdetermined mixture efficiently. Two-step approach Methods to solve SCA based BSS problems. It estimates the mixing matrix before the separation of the sources. K-means clustering is often used to estimate the mixing matrix. It relies on the prior knowledge of the source number strongly. However, the estimation of the source number is an obstacle. After this, the sources are recovered by the shortest path method (SPM). Simulations show the availability and robustness of the proposed method.
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