Abstract
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 However, the matrix which corresponds to within classes has been replaced by a new matrix.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 nonparametric forms, and is found to exhibit better classification in both cases over other parametric and nonparametric methods. With this new approach, the nonparametric method will prove to be more successful than its parametric counterpart. The feature selection is also discussed.
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Halet, A., Lampropoulos, G.A., Huynh, T. (1997). Target Classification by a New Class of Linear Discriminants. In: Lampropoulos, G.A., Lessard, R.A. (eds) Applications of Photonic Technology 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9250-8_105
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DOI: https://doi.org/10.1007/978-1-4757-9250-8_105
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