本文提出一种基于增广拉格朗日法的非线性约束优化算法用于独立成份分析(ICA), 仿真试验结果表明此方法可以有效的用于独立成份的分离. -This paper presents a broad-based increase Lagrange method of nonlinear constrained optimization algorithm for the independent component analysis (ICA), the simulation results show t

盲源分离算法的几篇文章应用 【基于独立分量分析的脑电中眼电伪迹消除】【基于负熵和智能优化的盲源分离方法】【基于小波消噪和盲源分离的信号奇异点检测方法】-Blind source separation algorithm applied 【several articles based on independent component analysis of EEG ocular artifact】 【intelligent optimization based on negative entr