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

doi:10.1007/s11460-010-0094-y

Front Elect Electr Eng Chin

2010, Vol. 5

Issue (4) : 488-492 https://doi.org/10.1007/s11460-010-0094-y

RESEARCH ARTICLE

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

Na SUN^1,2(

), Yajian ZHOU^1,2, Yixian YANG^1,2

1. Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; 2. Key Laboratory of Network and Information Attack and Defense Technology of Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China

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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

Corresponding Author(s): SUN Na,Email:sunna_07@163.com

Issue Date: 05 December 2010

Cite this article:

Na SUN,Yajian ZHOU,Yixian YANG. Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification[J]. Front Elect Electr Eng Chin, 2010, 5(4): 488-492.

URL:

https://academic.hep.com.cn/fee/EN/10.1007/s11460-010-0094-y
https://academic.hep.com.cn/fee/EN/Y2010/V5/I4/488

Fig.1 Recognition rates of polyspectral kernel

Tab.1 significances of attributes

Fig.2 Classification rate with

Fig.3 Significances of attributes (=0.4)

Fig.4 Classification rate with (weighted kernel)

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