Compressive Classification of Sparse Signal with Support Vector Machine

摘要：

Combining support vector machine (SVM) with compressive sensing (CS), a new classifier with compressive features is proposed. Based on this compressive classifier, a new method of classification is presented for the sparse modulated signals of 2FSK and 2ASK. Simulation results demonstrate that the performance of compressive classifier is close to that of traditional support vector classifier (SVC) with a significantly lower data requirement.

关键词： support vector machine compressive sensing signal classification

作者: HE Wei LI Yuebo LIU Feng

作者单位: The Third Engineer Research Institute of the Headquarters of the General Staff of PLA, Luoyang, Henan, 471023,China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 998-1001

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）