Radar target recognition based on a kernel double discriminant subspaces method

摘要

Kernel Fisher discriminant analysis (KFDA) is a very effective tool used for dimensionality reduction and feature extraction in pattern recognition. However, KFDA also suffers from the so-called small sample size problem (SSS) which often exists in high-d