%0 Journal Article
%T Study on Nonlinear Multifunctional Sensor Signal Reconstruction Method Based on LS-SVM<br>基于LS-SVM的非线性多功能传感器信号重构方法研究
%A WEI Guo
%A LIU Jian
%A SUN Jin-Wei
%A SUN Sheng-He
%A <br>魏国
%A LIU Jian
%A 孙金玮
%A SUN Sheng-He
%J 自动化学报
%D 2008
%I 
%X In this paper,the nonlinear multifunctional sensor signal reconstruction method based on the least squares support vector machine (LS-SVM) is proposed.Different from the reconstruction methods with empirical risk minimiza- tion,the support vector machine (SVM) is a new machine learning method based on structural risk minimization,which is applicable to the case of small sample size calibration data,and can efficiently restrain overfitting and improve general- ization capability.With SVM as a basis,the LS-SVM involves equality constraints instead of inequality constraints,so the solving process of the quadratic programming problem can be greatly simplified.In this study,L-fold cross validation is adopted to optimize the adjustable parameters.The reconstruction of input signals of a multifunctional sensor was carried out in two situations of different nonlinearities for which the reconstruction accuracies were 0.154 % and 1.146 %,respec- tively.The experimental results demonstrate the high reliability and high stability of the proposed LS-SVM reconstruction method,as well as the feasibility.
%K Multifunctional sensor
%K signal reconstruction
%K least squares support vector machine (LS-SVM)
%K cross validation<br>多功能传感器
%K 信号重构
%K 最小二乘支持向量机
%K 交叉验证
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=2F7FE93F0860FAB6449D915A857EDE48&yid=67289AFF6305E306&vid=339D79302DF62549&iid=5D311CA918CA9A03&sid=F26986CDF689DBC4&eid=4AA5FA7F666BDD0A&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=14