Individual Communication Transmitter Classification of Weighted Feature Set Based on RST

Feature extraction for individual communication transmitter identification is one of the major issues in the identifying process. A neighborhood rough set is proposed in this paper, in order to search for the good feature subset. Then we present a SVM classification approach of weighted feature set...

Full description

Saved in:
Bibliographic Details
Published in2009 Fourth International Conference on Internet Computing for Science and Engineering pp. 316 - 319
Main Authors Yajian Zhou, Sun Na, Yixian Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Computer networks
Data mining
feature selection
Information security
IP networks
Laboratories
neighborhood rough set
Random variables
support vector machine(SVM)
Support vector machines
Telecommunication computing
Telecommunication switching
transmitter identification
Transmitters
weighted feature set
Online AccessGet full text

Cover

More Information
Summary:Feature extraction for individual communication transmitter identification is one of the major issues in the identifying process. A neighborhood rough set is proposed in this paper, in order to search for the good feature subset. Then we present a SVM classification approach of weighted feature set based on the significance of an attribute. The result of experiments shows that the reduced feature subset is acquired ,and the classification accuracy of weighted feature subset is much better than that of non-weighted feature subset.
ISBN:9781424467549
1424467543
DOI:10.1109/ICICSE.2009.11