Using double-layer one-class classification for anti-jamming information filtering

Authors:
Qiang Sun;Jianhua Li;Xinran Liang;Shenghong Li
Affiliations:
Department of Electronic Engineering, Shanghai Jiao Tong University, China;Department of Electronic Engineering, Shanghai Jiao Tong University, China;ECE Department, UCSD, La Jolla, CA;Department of Electronic Engineering, Shanghai Jiao Tong University, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Abstract

One-class classification, a derivative of newly developed Support Vector Machine (SVM), obtains a spherically shaped boundary around a dataset, and the boundary can be made flexible by using kernel methods. In this paper, a new method is presented to improve the speed and accuracy of one-class classification. This method can be applied to anti-jamming information filtering with the aim of making it more practical. The experimental results show that the algorithm has better performance in general.