Compared with principal component analysis ( PCA) algorithm, the number of independent components is much smaller, meanwhile the independent components are informative for classification. 与传统的主成分分析特征提取算法相比,独立成分分析特征提取算法不仅进一步降低了特征的数目,而且分类精度也有显著提高。
The number of independent reaction is quite an important concept for studying the simultaneous equilibrium of many chemical reactions and in calculating the number of independent components and degree of freedom with correct use of the phase rule. 独立反应数对于研究多种化学反应同时平衡以及正确地使用相律计算相平衡体系的独立组分数、自由度数,都是一个十分重要的概念。
But ICA limits the number of input signals equivalent to or more than the number of independent components. 但是ICA本身也存在限制,要求输入信号个数大于或等于分离出独立分量的个数。