独立成分分析基本原理与发展

Principle and Development of Independent Component Analysis

独立成分分析是为解决盲源分离问题发展起来的一种高效的信号处理方法,广泛应用于国民经济发展和国防军事科学的各个领域。系统介绍了独立成分分析的基本模型、假设条件、解的不确定性问题,总结了目标函数的建立依据,如非高斯性最大化、互信息极小化和极大似然估计等,并简要总结了近年出现的独立成分分析优化方法,最后对独立成分分析的难点问题和未来可能的发展方向进行了总结和展望。

Independent component analysis is an efficient signal processing method widely used in various fields of national economic development and military science, and in particular, for solving the blind source separation problem. The basic model, assumption, uncertain solution, target function, optimization method, difficulties, and future development of this independent componet analysis are described and forecasted in the paper.