盲稀疏源信号分离算法的恢复性研究

On Recoverability of Blind Source Separation Based on Sparse Representation

基于一种两步稀疏表示的方法,利用随机框架讨论欠定盲源分离的恢复能力.盲稀疏源信号分离算法一般假设源信号是充分稀疏的,讨论了在源信号不充分稀疏的情况下欠定盲源分离的恢复能力的概率估计,进一步刻画了源的稀疏性与恢复能力的关系,揭示了利用两步法处理盲源分离问题的有效性.

This paper discusses the recoverability of underdetermined blind source separation （ BSS）, based on a two-stage sparse representation approach. Within the stochastic framework blind source separation it is usually predicted that source signals are sufficiently sparse. This paper estimates recoverability probability when source signals are not sufficiently sparse, which not only reflects the relationship between the recoverability and sparseness of sources but also indicates the effectiveness of the two-stage sparse representation approach to solving BSS.