Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
Mixed image cells decomposition algorithm based on principle component analysis is a widely used algorithm, but the large computation amount and less flexibility are its main drawbacks.
基于主分量分析的混合像元分解算法是一种较为成熟的算法，但它存在着计算量大，适应性差等缺点。
For this purpose, this paper presents a reuse cost optimization oriented, locality principle and instance set decomposition based component refactoring method.
为此，提出一种面向复用成本优化的、基于局部性原理与实例集分解的构件重构方法。
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