：介绍了独立成分分析(ICA)的基本模型及其假设、含混性、非高斯性度量和通用求解过程。讨论了目前ICA 的几个研究方向的发展现状和面临的问题，分析了ICA 基本模型和几种扩展模型的求解算法，包括盲反卷积、卷积混和的盲分离、非线性瞬时混合的盲分离。提出了ICA 未来理论和应用研究中的开放课题。-: Introduce the independent component analysis (ICA) the basic model and its assumptions, vague, non-Gaussian measurement and GM solving process. Discussion of the current ICA several research directions of the development of the current situation and the problems faced by an analysis of the basic ICA model and several extended model algorithm, including the blind deconvolution, convolution mixture of blind source separation, nonlinear transient mixed Blind Source Separation. Proposed ICA future theoretical and applied research topics in the open.