DocumentCode
2685281
Title
Research of Radar Range Profile´s Recognition Based on an Improved C-SVM Algorithm
Author
Ning, Fang ; Tao, Fan
Author_Institution
Coll. of Autom. & Electron. Inf., SUSE, Zigong, China
fYear
2012
fDate
27-29 Oct. 2012
Firstpage
801
Lastpage
804
Abstract
This paper improves upon Support Vector Machines (SVM) algorithm on unclassifiable sample sets condition for more to enhance its applicability, which is named after C-SVM (C is a parameter). One hand, non-equidistant margin hyper plane (NM) in high dimension eigen space is introduced to improve on study precision, On the other hand, effectual training sample sets in high dimension eigen space are filtrated, via algorithm introduced by this paper, to reduce study time. Above-mentioned methods are applied to Radar Range Profile´s Recognition, experimental results show that these methods can give very excellent recognition effect.
Keywords
pattern classification; radar computing; support vector machines; NM; effectual training sample sets; high dimension eigen space; improved C-SVM algorithm; nonequidistant margin hyperplane; radar range profile recognition; support vector machines; unclassifiable sample set condition; Classification algorithms; Partitioning algorithms; Pattern recognition; Radar; Support vector machines; Target recognition; Training; Eigen space; Non-equidistant margin hyperplane (NM); Radar Range Profile; Support Vector Machines (SVM);
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4673-4873-7
Type
conf
DOI
10.1109/CIT.2012.163
Filename
6392002
Link To Document