New technique for noisy target discrimination

摘要

A new linear discriminant technique that results in better classification performance over existing techniques is presented in this paper. This new approach is formulated in a similar manner to that of the Fisher linear discriminant. However, the matrix which corresponds to within classes has been replaced by a new matrix. This matrix takes into consideration the cross-correlation properties of the classes of interest. It has been shown through simulations that this matrix replacement results in a better classification performance over other linear discrimination methods, including the Fisher discriminant. Finally, the proposed new discriminant is presented in parametric and non-parametric forms, and is found to exhibit better classification in both cases over other parametric and non- parametric methods, respectively. With this new approach, the non-parametric method will prove to be more successful than its parametric counterpart.