Research on Feature Selection/Attribute Reduction Method Based on Rough Set Theory

摘要

Radar emitter signal is interfered by various noises during the propagation process, and the signal-to-noise ratio varies widely. Therefore, the features that play a key role in sorting and classifying or identification signals are often difficult to find. In addition, the extracted features are usually subjective and speculative, so it is necessary to select the features that can characterize the maximum difference mode information between the modulated signal categories and the changes in the signal-to-noise ratio. That is, the selected features also have good separability at low SNR. In this paper, based on rough set theory the feature selection method is studied, which lays a foundation for the feature selection of radiation source signals by rough set theory.