Infimum of features in number and feature selection of target recognition

Based on the attractor analysis approach in phase space, 7 kinds of general features are extracted from the Lorenz model system to compute the infimum of uncorrelated features in number by numerical experiments. This infimum indicates that the least number of features is feasible to classify samples of special target recognition completely. After the infimum is chosen, a new feature selection method - ordinal optimization is introduced and applied to the selection of the least and optimum feature group. Blind picking rule of ordinal optimization is tested in the experiments and the experimental results indicate that ordinal optimization can reduce the size of feature space quickly and efficiently, and is a feasible approach to search the satisfactory subset from huge feature combination space.