In order to deal with it, a fast feature vector select (FFVS) scheme is adopted that divides the total images into several groups according to.

Fast VQ algorithm for hyperspectral image compression based on feature selection;

A feature selection method based on ReliefF evaluation and complementary coefficient;

Application of union adaptive algorithm based on PCA and rough set for feature selection in face recognition;

After a brief introduction of the theories of Extension Matrix and Rough Set, Greedy Algorithm, and Heuristic search Algorithm, this paper compares their performance in signal feature extraction applications.

Traditional feature extraction method treats each feature separately and disregards the semantic feature such as relativity and comparability.

For features selection from infrared remote sensing image,the genetic algorithm(GA) is used to search for the optimum feature subset based on minimum entropy separability criterion.

On the base of Tibetn Character characteristic of graph construction,we explain what the peculiar processing in normalization,features selection and so on.