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.

Keywords

polyspectral kernel / support vector machine (SVM) / neighborhood rough set / weighted feature set / weighted kernel

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Higher Education Press and Springer-Verlag Berlin Heidelberg