【摘要】 分析了解决欠定盲源分离问题的稀疏分量分析方法。首先讨论了数据矩阵稀疏表示(分解)的方法,其次重点讨论了基于稀疏因式分解方法的盲源分离。该盲源分离技术分两步,一步是估计混合矩阵,第二步是估计源矩阵。如源信号是高度稀疏的,盲分离可直接在时域内实现。否则,对观测的混合矩阵运用小波包变换预处理后才能进行。仿真结果证明了理论分析的正确性。更多还原

【Abstract】 A sparse decomposition approach used in underdetermined BSS(Blind Source Separation)is presented.First,sparse representation(factorization) of a data matrix is discussed.Next,BSS is discussed based on sparse factorization approach.The blind separation technique includes two steps:estimating a mixing matrix and estimating sources.If the sources are sufficiently sparse,blind separation can be carried out directly in the time domain.Otherwise,blind separation can be implemented in time-frequency domain after applying wavelet packet transformation preprocessing to the observed mixtures.Theoretical considerations are supported by simulation results showing theoretical analysis is correct.更多还原