DocumentCode :
2538096
Title :
Recognition Method of Radar Signal Based on Rough Set and Support Vector Machine
Author :
Ting, Chen ; Jingqing, Luo
Author_Institution :
Electron. Eng. Inst., Hefei
fYear :
2007
fDate :
23-26 Oct. 2007
Firstpage :
486
Lastpage :
490
Abstract :
A hybrid algorithm based on attributes reduction of rough set and classification principles of support vector machine (SVM) is presented in this paper. Firstly, the attributes reduction of rough set has been applied as preprocessor so that we can delete the redundant attributes and conflicting objects from decision making table but remain efficient information lossless. Then, the classification modeling and forecasting test based on SVM are realized. By this method, the dimension of data is reduced greatly, the complexity in the process of SVM classification is decreased highly, the occupied memory is cut down and the over-fit of training model is prevented at some extent, also the good classification performance is obtained. Finally, the simulation experiment of radar signal recognition and its results show this hybrid method is effective.
Keywords :
radar computing; radar signal processing; rough set theory; support vector machines; SVM; classification modeling; forecasting test; radar signal recognition; recognition method; rough set; support vector machine; Data engineering; Data mining; Information processing; Power supplies; Radar signal processing; Radar theory; Signal analysis; Signal processing; Support vector machines; Training data; SVM; attributes reduction; kernel function; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electromagnetic Compatibility, 2007. EMC 2007. International Symposium on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-1371-3
Electronic_ISBN :
978-1-4244-1372-0
Type :
conf
DOI :
10.1109/ELMAGC.2007.4413537
Filename :
4413537
Link To Document :
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