Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification

Abstract

This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved.